Applied Researcher II Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Publications studying tokenization, data quality, dataset curation, or labeling Contribution to a major open source corpus Contribution to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II Cambridge, MA: $262,500 - $299,600 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation . click apply for full job details
09/14/2026
Full time
Applied Researcher II Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Publications studying tokenization, data quality, dataset curation, or labeling Contribution to a major open source corpus Contribution to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II Cambridge, MA: $262,500 - $299,600 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation . click apply for full job details
Applied Researcher I (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher I (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Applied Researcher I (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher I (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Senior Director, Applied Research Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. This is a people manager role that will lead teams to drive strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected people leader, you will guide and mentor a team of applied scientists. You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate : You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Key Responsibilities: Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Basic Qualifications: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research At least 5 years of people leadership experience Preferred Qualifications choose applicable set based on focus of role : PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 10 years of industrial NLP research experience Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Has worked on an LLM (open source or commercial) that is currently available for use Demonstrated ability to guide the technical direction of a large-scale model training team Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens Experience with common training optimization frameworks (deep speed, nemo) Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Member of technical leadership for model deployment for a very large user behavior model Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large language models 5+ years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Numerous Publications studying tokenization, data quality, dataset curation, or labeling Leading contributions to one or more large open source corpus (1 Trillion + tokens) Core contributor to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $318,100 - $363,100 for Sr Director, Applied Research Cambridge, MA: $350,000 - $399,500 for Sr Director, Applied Research McLean, VA: $350,000 - $399,500 for Sr Director, Applied Research New York, NY: $381,800 - $435,700 for Sr Director, Applied Research Richmond, VA: $318,100 - $363,100 for Sr Director, Applied Research San Francisco, CA: $381,800 - $435,700 for Sr Director . click apply for full job details
09/14/2026
Full time
Senior Director, Applied Research Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. This is a people manager role that will lead teams to drive strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected people leader, you will guide and mentor a team of applied scientists. You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate : You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Key Responsibilities: Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Basic Qualifications: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research At least 5 years of people leadership experience Preferred Qualifications choose applicable set based on focus of role : PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 10 years of industrial NLP research experience Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Has worked on an LLM (open source or commercial) that is currently available for use Demonstrated ability to guide the technical direction of a large-scale model training team Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens Experience with common training optimization frameworks (deep speed, nemo) Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Member of technical leadership for model deployment for a very large user behavior model Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large language models 5+ years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Numerous Publications studying tokenization, data quality, dataset curation, or labeling Leading contributions to one or more large open source corpus (1 Trillion + tokens) Core contributor to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $318,100 - $363,100 for Sr Director, Applied Research Cambridge, MA: $350,000 - $399,500 for Sr Director, Applied Research McLean, VA: $350,000 - $399,500 for Sr Director, Applied Research New York, NY: $381,800 - $435,700 for Sr Director, Applied Research Richmond, VA: $318,100 - $363,100 for Sr Director, Applied Research San Francisco, CA: $381,800 - $435,700 for Sr Director . click apply for full job details
Applied Researcher II (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher II McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher II (AI Foundations, LLM Core and Agentic AI) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher II McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Applied Researcher I (AI Foundations) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher I (AI Foundations) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Applied Researcher I (AI Foundations, VLM) At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher I (AI Foundations, VLM) At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with high quality ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, a PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 2 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $218,700 - $249,600 for Applied Researcher I McLean, VA: $218,700 - $249,600 for Applied Researcher I New York, NY: $238,600 - $272,300 for Applied Researcher I San Francisco, CA: $238,600 - $272,300 for Applied Researcher I San Jose, CA: $238,600 - $272,300 for Applied Researcher I Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Director, AI Engineering (Remote - eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. About the Team This team owns the infrastructure layer between applications and foundation models: model access, routing, reliability, security integration, observability, and cost management behind a single governed interface. Product teams build on the platform instead of integrating with model providers directly, which means the enterprise adopts new model capability once, centrally, rather than many times over. Sitting in the request path for every AI-powered application makes latency, reliability, and efficiency company-level outcomes rather than local ones. This team also owns a measurement and attribution layer that makes consumption legible to the optimization capabilities that act on it, including intelligent routing, caching, context optimization, and capacity planning. The objective is cost per unit of business outcome, not spend reduction in isolation. The architecture set now will determine the enterprise's cost curve and build velocity for years, and this role owns both those decisions and the teams that execute them. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing or leading AI and ML algorithms or technologies At least 3 years of people leadership experience Preferred Qualifications: 5 years of experience managing and leading an engineering team 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Master's degree in Computer Science, Computer Engineering, or relevant technical field Passion for staying up to date with the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineering McLean, VA: $269,100 - $307,200 for Director, AI Engineering New York, NY: $293,600 - $335,100 for Director, AI Engineering San Francisco, CA: $293,600 - $335,100 for Director, AI Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Director, AI Engineering (Remote - eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. About the Team This team owns the infrastructure layer between applications and foundation models: model access, routing, reliability, security integration, observability, and cost management behind a single governed interface. Product teams build on the platform instead of integrating with model providers directly, which means the enterprise adopts new model capability once, centrally, rather than many times over. Sitting in the request path for every AI-powered application makes latency, reliability, and efficiency company-level outcomes rather than local ones. This team also owns a measurement and attribution layer that makes consumption legible to the optimization capabilities that act on it, including intelligent routing, caching, context optimization, and capacity planning. The objective is cost per unit of business outcome, not spend reduction in isolation. The architecture set now will determine the enterprise's cost curve and build velocity for years, and this role owns both those decisions and the teams that execute them. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing or leading AI and ML algorithms or technologies At least 3 years of people leadership experience Preferred Qualifications: 5 years of experience managing and leading an engineering team 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Master's degree in Computer Science, Computer Engineering, or relevant technical field Passion for staying up to date with the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineering McLean, VA: $269,100 - $307,200 for Director, AI Engineering New York, NY: $293,600 - $335,100 for Director, AI Engineering San Francisco, CA: $293,600 - $335,100 for Director, AI Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Applied Researcher II (AI Foundations) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPS, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked with datasets with 100m+ users Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Publications studying tokenization, data quality, dataset curation, or labeling Contribution to a major open source corpus Contribution to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher II McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher II (AI Foundations) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPS, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked with datasets with 100m+ users Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Publications studying tokenization, data quality, dataset curation, or labeling Contribution to a major open source corpus Contribution to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher II McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II San Francisco, CA: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Janssen Research & Development, LLC
Ambler, Pennsylvania
Job Title: Senior Engineer, Machine Learning Research and Development Job Code: A011.9806 Job Location: Spring House, PA Job Type: Full-Time Job Duties: Develop strategic roadmap and capabilities for applied AI/ML in Biopharmaceutical development. Build novel machine learning models focused on helping development project teams make best decisions from data. Deliver solutions with user functionality to enable project teams to use models and consult with model builders. Work with business functions and IT to develop data flow enabling data block generation supporting modeling. Advise project teams on data driven decision making including design of experiments, investigations, transforming historical data to knowledge. Collaborate with scientists and build roadmap and capabilities where modeling can be applied to enable faster, more robust biologics process development in the CMC space. Leverage experience in applied machine learning and artificial-intelligence applications to define opportunities for changing the way we work. Ensure output of models meet project teams needs and invigorates generation of intellectual property that solidifies and improves the company's ability to deliver and accelerates development to meet patient needs. May telecommute per company's policy (hybrid). Requirements: Employer will accept a Ph.D. degree in Science, Industrial Engineering and Operations Research, Data Science, (AI/ML) or related field and 2 years of experience in the job offered or in a Senior Engineer, Machine Learning Research and Development-related occupation. Position requires experience in: 1. Advanced therapies in science, development and production processes. 2. Leading strategic modeling programs and delivering solutions. 3. Utilizing strategic approaches to apply the best modeling techniques and leverage recent literature. 4. Applying machine learning modeling to support biopharmaceutical industry. 5. Programming languages including .net, Java, Perl, C++, Matlab, R, Julia or Python. 6. Wrangling and transforming high dimensional big data from established data warehouses. 7. Statistics, algorithm design, and module verification and validation. 8. Applying agile and waterfall approach SDLC. 9. JIRA, git, scrum, or confluence. 10. Principle and application of LLM (Large Language Models). 11. Cloud platforms including Azure or Amazon Web Services (AWS), or full-stack development. Contact: Send resume to (email removed) & refer to .9806
09/14/2026
Job Title: Senior Engineer, Machine Learning Research and Development Job Code: A011.9806 Job Location: Spring House, PA Job Type: Full-Time Job Duties: Develop strategic roadmap and capabilities for applied AI/ML in Biopharmaceutical development. Build novel machine learning models focused on helping development project teams make best decisions from data. Deliver solutions with user functionality to enable project teams to use models and consult with model builders. Work with business functions and IT to develop data flow enabling data block generation supporting modeling. Advise project teams on data driven decision making including design of experiments, investigations, transforming historical data to knowledge. Collaborate with scientists and build roadmap and capabilities where modeling can be applied to enable faster, more robust biologics process development in the CMC space. Leverage experience in applied machine learning and artificial-intelligence applications to define opportunities for changing the way we work. Ensure output of models meet project teams needs and invigorates generation of intellectual property that solidifies and improves the company's ability to deliver and accelerates development to meet patient needs. May telecommute per company's policy (hybrid). Requirements: Employer will accept a Ph.D. degree in Science, Industrial Engineering and Operations Research, Data Science, (AI/ML) or related field and 2 years of experience in the job offered or in a Senior Engineer, Machine Learning Research and Development-related occupation. Position requires experience in: 1. Advanced therapies in science, development and production processes. 2. Leading strategic modeling programs and delivering solutions. 3. Utilizing strategic approaches to apply the best modeling techniques and leverage recent literature. 4. Applying machine learning modeling to support biopharmaceutical industry. 5. Programming languages including .net, Java, Perl, C++, Matlab, R, Julia or Python. 6. Wrangling and transforming high dimensional big data from established data warehouses. 7. Statistics, algorithm design, and module verification and validation. 8. Applying agile and waterfall approach SDLC. 9. JIRA, git, scrum, or confluence. 10. Principle and application of LLM (Large Language Models). 11. Cloud platforms including Azure or Amazon Web Services (AWS), or full-stack development. Contact: Send resume to (email removed) & refer to .9806
Senior Director, Applied Research Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. This is a people manager role that will lead teams to drive strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected people leader, you will guide and mentor a team of applied scientists. You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate : You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Key Responsibilities: Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Basic Qualifications: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research At least 5 years of people leadership experience Preferred Qualifications choose applicable set based on focus of role : PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 10 years of industrial NLP research experience Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Has worked on an LLM (open source or commercial) that is currently available for use Demonstrated ability to guide the technical direction of a large-scale model training team Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens Experience with common training optimization frameworks (deep speed, nemo) Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Member of technical leadership for model deployment for a very large user behavior model Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large language models 5+ years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Numerous Publications studying tokenization, data quality, dataset curation, or labeling Leading contributions to one or more large open source corpus (1 Trillion + tokens) Core contributor to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $318,100 - $363,100 for Sr Director, Applied Research Cambridge, MA: $350,000 - $399,500 for Sr Director, Applied Research McLean, VA: $350,000 - $399,500 for Sr Director, Applied Research New York, NY: $381,800 - $435,700 for Sr Director, Applied Research Richmond, VA: $318,100 - $363,100 for Sr Director, Applied Research San Francisco, CA: $381,800 - $435,700 for Sr Director . click apply for full job details
09/14/2026
Full time
Senior Director, Applied Research Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. This is a people manager role that will lead teams to drive strategic direction through collaboration with Applied Science, Engineering and Product leaders across Capital One. As a well-respected people leader, you will guide and mentor a team of applied scientists. You will be expected to be an external leader representing Capital One in the research community, collaborating with prominent faculty members in the relevant AI research community. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate : You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Key Responsibilities: Partner with a cross-functional team of scientists, machine learning engineers, software engineers, and product managers to deliver AI-powered platforms and solutions that change how customers interact with their money. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. Basic Qualifications: PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 6 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 8 years of experience in Applied Research At least 5 years of people leadership experience Preferred Qualifications choose applicable set based on focus of role : PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 10 years of industrial NLP research experience Core contributor to team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Numerous publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Has worked on an LLM (open source or commercial) that is currently available for use Demonstrated ability to guide the technical direction of a large-scale model training team Experience working with 500+ node clusters of GPUs Has worked on LLM scaled to 70B parameters and 1T+ tokens Experience with common training optimization frameworks (deep speed, nemo) Behavioral Models PhD focus on topics in geometric deep learning (Graph Neural Networks, Sequential Models, Multivariate Time Series) Member of technical leadership for model deployment for a very large user behavior model Multiple papers on topics relevant to training models on graph and sequential data structures at KDD, ICML, NeurIPs, ICLR Worked on scaling graph models to greater than 50m nodes Experience with large scale deep learning based recommender systems Experience with production real-time and streaming environments Contributions to common open source frameworks (pytorch-geometric, DGL) Proposed new methods for inference or representation learning on graphs or sequences Worked datasets with 100m+ users Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large language models 5+ years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Data Preparation Numerous Publications studying tokenization, data quality, dataset curation, or labeling Leading contributions to one or more large open source corpus (1 Trillion + tokens) Core contributor to open source libraries for data quality, dataset curation, or labeling Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Sales Territory: $318,100 - $363,100 for Sr Director, Applied Research Cambridge, MA: $350,000 - $399,500 for Sr Director, Applied Research McLean, VA: $350,000 - $399,500 for Sr Director, Applied Research New York, NY: $381,800 - $435,700 for Sr Director, Applied Research Richmond, VA: $318,100 - $363,100 for Sr Director, Applied Research San Francisco, CA: $381,800 - $435,700 for Sr Director . click apply for full job details
Applied Researcher II (AI Foundations) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher II McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Applied Researcher II (AI Foundations) Overview: At Capital One, we are creating trustworthy and reliable AI systems, changing banking for good. For years, Capital One has been leading the industry in using machine learning to create real-time, intelligent, automated customer experiences. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to building world-class applied science and engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The AI Foundations team is at the center of bringing our vision for AI at Capital One to life. Our work touches every aspect of the research life cycle, from partnering with Academia to building production systems. We work with product, technology and business leaders to apply the state of the art in AI to our business. In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Huggingface, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. Build AI foundation models through all phases of development, from design through training, evaluation, validation, and implementation. Engage in high impact applied research to take the latest AI developments and push them into the next generation of customer experiences. Flex your interpersonal skills to translate the complexity of your work into tangible business goals. The Ideal Candidate: You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers. Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea. A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing AI foundation models and solutions using open-source tools and cloud computing platforms. Has a deep understanding of the foundations of AI methodologies. Experience building large deep learning models, whether on language, images, events, or graphs, as well as expertise in one or more of the following: training optimization, self-supervised learning, robustness, explainability, RLHF. An engineering mindset as shown by a track record of delivering models at scale both in terms of training data and inference volumes. Experience in delivering libraries, platform level code or solution level code to existing products. A professional with a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects. Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects. Basic Qualifications: Currently has, or is in the process of obtaining, PhD in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields, with an exception that required degree will be obtained on or before the scheduled start date plus 2 years of experience in Applied Research or M.S. in Electrical Engineering, Computer Engineering, Computer Science, AI, Mathematics, or related fields plus 4 years of experience in Applied Research Preferred Qualifications: PhD in Computer Science, Machine Learning, Computer Engineering, Applied Mathematics, Electrical Engineering or related fields LLM PhD focus on NLP or Masters with 5 years of industrial NLP research experience Multiple publications on topics related to the pre-training of large language models (e.g. technical reports of pre-trained LLMs, SSL techniques, model pre-training optimization) Member of team that has trained a large language model from scratch (10B + parameters, 500B+ tokens) Publications in deep learning theory Publications at ACL, NAACL and EMNLP, Neurips, ICML or ICLR Optimization (Training & Inference) PhD focused on topics related to optimizing training of very large deep learning models Multiple years of experience and/or publications on one of the following topics: Model Sparsification, Quantization, Training Parallelism/Partitioning Design, Gradient Checkpointing, Model Compression Experience optimizing training for a 10B+ model Deep knowledge of deep learning algorithmic and/or optimizer design Experience with compiler design Finetuning PhD focused on topics related to guiding LLMs with further tasks (Supervised Finetuning, Instruction-Tuning, Dialogue-Finetuning, Parameter Tuning) Demonstrated knowledge of principles of transfer learning, model adaptation and model guidance Experience deploying a fine-tuned large language model Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $262,500 - $299,600 for Applied Researcher II McLean, VA: $262,500 - $299,600 for Applied Researcher II New York, NY: $286,400 - $326,800 for Applied Researcher II San Jose, CA: $286,400 - $326,800 for Applied Researcher II Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Director, AI Engineering (Remote - eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. About the Team This team owns the infrastructure layer between applications and foundation models: model access, routing, reliability, security integration, observability, and cost management behind a single governed interface. Product teams build on the platform instead of integrating with model providers directly, which means the enterprise adopts new model capability once, centrally, rather than many times over. Sitting in the request path for every AI-powered application makes latency, reliability, and efficiency company-level outcomes rather than local ones. This team also owns a measurement and attribution layer that makes consumption legible to the optimization capabilities that act on it, including intelligent routing, caching, context optimization, and capacity planning. The objective is cost per unit of business outcome, not spend reduction in isolation. The architecture set now will determine the enterprise's cost curve and build velocity for years, and this role owns both those decisions and the teams that execute them. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing or leading AI and ML algorithms or technologies At least 3 years of people leadership experience Preferred Qualifications: 5 years of experience managing and leading an engineering team 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Master's degree in Computer Science, Computer Engineering, or relevant technical field Passion for staying up to date with the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineering McLean, VA: $269,100 - $307,200 for Director, AI Engineering New York, NY: $293,600 - $335,100 for Director, AI Engineering San Francisco, CA: $293,600 - $335,100 for Director, AI Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
09/14/2026
Full time
Director, AI Engineering (Remote - eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. About the Team This team owns the infrastructure layer between applications and foundation models: model access, routing, reliability, security integration, observability, and cost management behind a single governed interface. Product teams build on the platform instead of integrating with model providers directly, which means the enterprise adopts new model capability once, centrally, rather than many times over. Sitting in the request path for every AI-powered application makes latency, reliability, and efficiency company-level outcomes rather than local ones. This team also owns a measurement and attribution layer that makes consumption legible to the optimization capabilities that act on it, including intelligent routing, caching, context optimization, and capacity planning. The objective is cost per unit of business outcome, not spend reduction in isolation. The architecture set now will determine the enterprise's cost curve and build velocity for years, and this role owns both those decisions and the teams that execute them. In this role, you will: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Basic Qualifications: Bachelor's degree in Computer Science, Engineering, or AI plus at least 8 years of experience developing or leading AI and ML algorithms or technologies, or Master's degree plus at least 6 years of experience developing or leading AI and ML algorithms or technologies At least 3 years of people leadership experience Preferred Qualifications: 5 years of experience managing and leading an engineering team 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) Master's degree in Computer Science, Computer Engineering, or relevant technical field Passion for staying up to date with the latest AI research and AI systems, and judiciously apply novel techniques in production Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineering McLean, VA: $269,100 - $307,200 for Director, AI Engineering New York, NY: $293,600 - $335,100 for Director, AI Engineering San Francisco, CA: $293,600 - $335,100 for Director, AI Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections ; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1- or via email at . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).
Job Description Job Description Title: RF Wireless Engineer (Contract) Pay Rate: up to $51.43/hour Duration: 12-Month Assignment (Potential to Extend or Convert) Hours: Full-Time Start Date: ASAP Location: Carlsbad, CA (Onsite) Summary We are seeking an experienced RF Wireless Engineer to support the design, integration, testing, and optimization of next-generation wireless connectivity solutions for smart consumer devices. This hands-on engineering role will focus on RF hardware development, antenna performance, wireless protocol validation, and system-level integration across multiple wireless technologies. The ideal candidate has a strong background in RF circuit design, antenna tuning, and wireless communications, along with experience bringing consumer electronics products from development through production. This position offers the opportunity to work closely with firmware, hardware, manufacturing, and quality teams to deliver high-performance wireless products. What You'll Do • Develop, integrate, and optimize RF hardware supporting Wi-Fi, Thread, Zigbee, Z-Wave, LTE, and other wireless technologies • Perform bring-up, debugging, validation, and optimization of wireless MAC and PHY layer drivers and firmware • Design, tune, and optimize antennas for Wi-Fi, Bluetooth, NFC, GNSS, cellular, and additional wireless communication technologies • Perform antenna tuning, impedance matching, efficiency optimization, TRP/TIS characterization, and RF performance analysis • Design and review RF PCB layouts, including controlled impedance routing, grounding, shielding, stack-up design, and antenna keep-out requirements • Collaborate with Firmware, Quality Assurance, Manufacturing, and external development partners to resolve product performance issues and ensure successful product integration • Develop and execute RF validation plans supporting wireless protocol performance and regulatory compliance • Analyze and troubleshoot RF system issues including EMI, spurious emissions, desense, ESD, current consumption, and in-band noise • Support prototype builds, hardware bring-up, product validation, and production readiness activities • Utilize laboratory equipment to perform hardware testing, component rework, soldering, and detailed debugging of RF assemblies What You Bring • Bachelor's degree in Electrical Engineering, Electronics Engineering, RF Engineering, or a related discipline • 5+ years of experience designing and integrating RF hardware for consumer electronic products • Strong experience with Wi-Fi (802.11), 802.15.4, Thread, Zigbee, Z-Wave, LTE, or similar wireless communication technologies • Hands-on experience with antenna design, tuning, impedance matching, and RF optimization • Strong understanding of RF fundamentals including transmission lines, S-parameters, antenna matching, and RF measurements • Experience designing RF circuits and supporting system integration, validation, and production • Knowledge of RF PCB layout best practices, including controlled impedance routing, grounding, shielding, and antenna placement • Experience validating wireless performance across multiple 802.11 standards (a/b/g/n/ac/ax/ah) • Strong troubleshooting skills related to RF performance, EMI, desense, ESD, power consumption, and wireless system optimization • Experience using RF test equipment and laboratory tools, including soldering stations, microscopes, and SMT component rework • Excellent communication skills with the ability to collaborate across engineering, manufacturing, and quality teams Bonus Points If You Have • Experience with IoT product development and connected consumer devices • Experience integrating antennas into compact electronic products • Experience supporting high-volume consumer electronics manufacturing • Familiarity with regulatory and wireless certification testing • Experience working with external manufacturing or ODM partners • Experience developing products on rapid 6-12 month development cycles TCWGlobal is an equal opportunity employer. We do not discriminate based on age, ethnicity, gender, nationality, religious belief, or sexual orientation. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
09/14/2026
Full time
Job Description Job Description Title: RF Wireless Engineer (Contract) Pay Rate: up to $51.43/hour Duration: 12-Month Assignment (Potential to Extend or Convert) Hours: Full-Time Start Date: ASAP Location: Carlsbad, CA (Onsite) Summary We are seeking an experienced RF Wireless Engineer to support the design, integration, testing, and optimization of next-generation wireless connectivity solutions for smart consumer devices. This hands-on engineering role will focus on RF hardware development, antenna performance, wireless protocol validation, and system-level integration across multiple wireless technologies. The ideal candidate has a strong background in RF circuit design, antenna tuning, and wireless communications, along with experience bringing consumer electronics products from development through production. This position offers the opportunity to work closely with firmware, hardware, manufacturing, and quality teams to deliver high-performance wireless products. What You'll Do • Develop, integrate, and optimize RF hardware supporting Wi-Fi, Thread, Zigbee, Z-Wave, LTE, and other wireless technologies • Perform bring-up, debugging, validation, and optimization of wireless MAC and PHY layer drivers and firmware • Design, tune, and optimize antennas for Wi-Fi, Bluetooth, NFC, GNSS, cellular, and additional wireless communication technologies • Perform antenna tuning, impedance matching, efficiency optimization, TRP/TIS characterization, and RF performance analysis • Design and review RF PCB layouts, including controlled impedance routing, grounding, shielding, stack-up design, and antenna keep-out requirements • Collaborate with Firmware, Quality Assurance, Manufacturing, and external development partners to resolve product performance issues and ensure successful product integration • Develop and execute RF validation plans supporting wireless protocol performance and regulatory compliance • Analyze and troubleshoot RF system issues including EMI, spurious emissions, desense, ESD, current consumption, and in-band noise • Support prototype builds, hardware bring-up, product validation, and production readiness activities • Utilize laboratory equipment to perform hardware testing, component rework, soldering, and detailed debugging of RF assemblies What You Bring • Bachelor's degree in Electrical Engineering, Electronics Engineering, RF Engineering, or a related discipline • 5+ years of experience designing and integrating RF hardware for consumer electronic products • Strong experience with Wi-Fi (802.11), 802.15.4, Thread, Zigbee, Z-Wave, LTE, or similar wireless communication technologies • Hands-on experience with antenna design, tuning, impedance matching, and RF optimization • Strong understanding of RF fundamentals including transmission lines, S-parameters, antenna matching, and RF measurements • Experience designing RF circuits and supporting system integration, validation, and production • Knowledge of RF PCB layout best practices, including controlled impedance routing, grounding, shielding, and antenna placement • Experience validating wireless performance across multiple 802.11 standards (a/b/g/n/ac/ax/ah) • Strong troubleshooting skills related to RF performance, EMI, desense, ESD, power consumption, and wireless system optimization • Experience using RF test equipment and laboratory tools, including soldering stations, microscopes, and SMT component rework • Excellent communication skills with the ability to collaborate across engineering, manufacturing, and quality teams Bonus Points If You Have • Experience with IoT product development and connected consumer devices • Experience integrating antennas into compact electronic products • Experience supporting high-volume consumer electronics manufacturing • Familiarity with regulatory and wireless certification testing • Experience working with external manufacturing or ODM partners • Experience developing products on rapid 6-12 month development cycles TCWGlobal is an equal opportunity employer. We do not discriminate based on age, ethnicity, gender, nationality, religious belief, or sexual orientation. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Job Description Job Description Director of Product Design Location: St. Louis, MO (On-site) About KNOWiNK KNOWiNK builds technology that powers elections. Our products are trusted by election officials across the country to run accurate, efficient, and accessible elections, forming a foundation for democratic participation. We are an AI-forward company committed to continuous innovation, and we build software that serves a wide range of users: from poll workers managing a busy precinct on Election Day to county clerks who depend on our tools day in and day out. Designing for this mission demands rigor, empathy, and an unwavering commitment to clarity. Role Overview The Director of Product Design is a senior leadership role responsible for the strategy, quality, and execution of user experience across KNOWiNK's suite of election products. This role owns KNOWiNK's design vision, shaping the experiences that ultimately touch tens of millions of voters across the country. The Director leads a team of three UX designers and operates as a player/coach, contributing hands-on design work on cross-functional teams while setting the direction, standards, and processes that elevate the entire design function. The Director of Product Design will report to the Director of Product and work closely with Engineering and Product leadership to define and continuously refine the processes, standards, and direction that enable the team to deliver great user experiences across KNOWiNK's product portfolio, spanning web and native iPadOS applications. A primary objective of this role is to unify a product portfolio that has historically felt fragmented, bringing consistency, coherence, and a shared design identity across all KNOWiNK products. Key Responsibilities Team Leadership & Development Lead, mentor, and develop a team of three UX designers, ensuring work quality meetsKNOWiNK'sstandards and each designer is growing in their craft Make decisions about designer assignments to cross-functional (XFN) teams, ensuring effective design coverage across the product portfolio Foster a culture of feedback, craft, and continuous improvement within the design team Design Strategy & Execution Own the end-to-end user experience strategy acrossKNOWiNK'sproduct suite, with a clear mandate to achieve consistency and coherence across historically fragmented products Lead and mature theKNOWiNKdesign system, driving adoption across all product teams and technology stacks Contribute directly as a designer on cross-functional teams, delivering high-quality UX work alongside your team Design for a diverse set of user personas, including poll workers who requirehighly accessible, self-explanatory interfaces, and county clerks who prioritize speed and efficiency Uphold and advance accessibility standards across all products, ensuring compliance with ADA and WCAG guidelines Champion a culture of rapid prototyping and continuous user feedback,establishinglightweight research practices thatvalidatedesign decisions early and reduce the risk of building the wrong thing Cross-Functional Collaboration Establish and lead cross-functional design standards in partnership with Engineering and Product Ensure Design is integrated throughout the SDLC, including contributing to the definition of Ready and definition of Done Collaborate with Product and Engineering leadership to align on roadmap priorities and delivery expectations Process, Tooling & AI Define and own design team processes, workflows, and tooling decisions Champion the use of AI in design, setting clear standards for how AI tools should and should not beleveragedby the design team Stay current on emerging design tools and methodologies and evaluate their applicability toKNOWiNK'sworkflows Qualifications Required 7+ years of UX/product design experience, with at least 2 years in a people management role (design manager, design lead, or director) Demonstrated experience designing software products, with a strong portfolio showing end-to-end product design work Experience leading or contributing significantly to a design system in a multi-product environment Proven ability to drive design consistency across a portfolio of products Strong collaboration skills with Engineering and Product counterparts, including experience working within an agile SDLC Experience designing for diverse user personas with varying technical sophistication Solid foundation in accessibility standards and inclusive design principles Comfortable operating as a player/coach, both leading the team and contributing hands-on design work Preferred Experience designing for native mobile or iPadOS applications Familiarity with AI-assisted design tools and a perspective on responsible AI use in design workflows Experience working across products at varying stages of maturity and go-to-market readiness Location This position is fully on-site at KNOWiNK's headquarters in St. Louis, Missouri. Remote and hybrid arrangements are not available for this role.
09/13/2026
Full time
Job Description Job Description Director of Product Design Location: St. Louis, MO (On-site) About KNOWiNK KNOWiNK builds technology that powers elections. Our products are trusted by election officials across the country to run accurate, efficient, and accessible elections, forming a foundation for democratic participation. We are an AI-forward company committed to continuous innovation, and we build software that serves a wide range of users: from poll workers managing a busy precinct on Election Day to county clerks who depend on our tools day in and day out. Designing for this mission demands rigor, empathy, and an unwavering commitment to clarity. Role Overview The Director of Product Design is a senior leadership role responsible for the strategy, quality, and execution of user experience across KNOWiNK's suite of election products. This role owns KNOWiNK's design vision, shaping the experiences that ultimately touch tens of millions of voters across the country. The Director leads a team of three UX designers and operates as a player/coach, contributing hands-on design work on cross-functional teams while setting the direction, standards, and processes that elevate the entire design function. The Director of Product Design will report to the Director of Product and work closely with Engineering and Product leadership to define and continuously refine the processes, standards, and direction that enable the team to deliver great user experiences across KNOWiNK's product portfolio, spanning web and native iPadOS applications. A primary objective of this role is to unify a product portfolio that has historically felt fragmented, bringing consistency, coherence, and a shared design identity across all KNOWiNK products. Key Responsibilities Team Leadership & Development Lead, mentor, and develop a team of three UX designers, ensuring work quality meetsKNOWiNK'sstandards and each designer is growing in their craft Make decisions about designer assignments to cross-functional (XFN) teams, ensuring effective design coverage across the product portfolio Foster a culture of feedback, craft, and continuous improvement within the design team Design Strategy & Execution Own the end-to-end user experience strategy acrossKNOWiNK'sproduct suite, with a clear mandate to achieve consistency and coherence across historically fragmented products Lead and mature theKNOWiNKdesign system, driving adoption across all product teams and technology stacks Contribute directly as a designer on cross-functional teams, delivering high-quality UX work alongside your team Design for a diverse set of user personas, including poll workers who requirehighly accessible, self-explanatory interfaces, and county clerks who prioritize speed and efficiency Uphold and advance accessibility standards across all products, ensuring compliance with ADA and WCAG guidelines Champion a culture of rapid prototyping and continuous user feedback,establishinglightweight research practices thatvalidatedesign decisions early and reduce the risk of building the wrong thing Cross-Functional Collaboration Establish and lead cross-functional design standards in partnership with Engineering and Product Ensure Design is integrated throughout the SDLC, including contributing to the definition of Ready and definition of Done Collaborate with Product and Engineering leadership to align on roadmap priorities and delivery expectations Process, Tooling & AI Define and own design team processes, workflows, and tooling decisions Champion the use of AI in design, setting clear standards for how AI tools should and should not beleveragedby the design team Stay current on emerging design tools and methodologies and evaluate their applicability toKNOWiNK'sworkflows Qualifications Required 7+ years of UX/product design experience, with at least 2 years in a people management role (design manager, design lead, or director) Demonstrated experience designing software products, with a strong portfolio showing end-to-end product design work Experience leading or contributing significantly to a design system in a multi-product environment Proven ability to drive design consistency across a portfolio of products Strong collaboration skills with Engineering and Product counterparts, including experience working within an agile SDLC Experience designing for diverse user personas with varying technical sophistication Solid foundation in accessibility standards and inclusive design principles Comfortable operating as a player/coach, both leading the team and contributing hands-on design work Preferred Experience designing for native mobile or iPadOS applications Familiarity with AI-assisted design tools and a perspective on responsible AI use in design workflows Experience working across products at varying stages of maturity and go-to-market readiness Location This position is fully on-site at KNOWiNK's headquarters in St. Louis, Missouri. Remote and hybrid arrangements are not available for this role.
Utility Computing (UC) AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. EC2 Nitro drives the planet's largest, fastest growing and most feature-rich compute cloud. Nitro is AWS's ground-up design for virtualization at global scale built on a fully custom stack of hardware, firmware and applications. Nitro has enabled EC2 to support Intel, AMD and Amazon's custom silicon - Graviton3 - while raising the industry bar for security and performance across our product line. The Nitro Team is looking for engineers with systems knowledge and experience in area such as Linux OS boot sequencing, Kernel, Hypervisor (Xen or KVM), peripheral device development (PCIe or NVMe) and building compute infrastructure to support High Memory and High performance computing workloads. The Nitro High Memory and HPC team owns the purpose built platform development for the High performance computing workloads and database workloads like SAP, Oracle and SQL with tens of terra-byte of memories. Team interfaces directly with system BIOS for bare-metal instances and drives critical system interactions within the Nitro Hypervisor and across EC2 control-plane services. We need engineers with the dive-deep and ownership to work across domains (such as PC peripheral firmware or Linux Kernel internals) to deliver features and new instance types for our customers. Work is typically done in C/C++ or Rust with supporting script and tests in Python and Lua. About the Team Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 10017 BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CA, SANTA CLARA - 165 600.00 USD annually
09/13/2026
Full time
Utility Computing (UC) AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. EC2 Nitro drives the planet's largest, fastest growing and most feature-rich compute cloud. Nitro is AWS's ground-up design for virtualization at global scale built on a fully custom stack of hardware, firmware and applications. Nitro has enabled EC2 to support Intel, AMD and Amazon's custom silicon - Graviton3 - while raising the industry bar for security and performance across our product line. The Nitro Team is looking for engineers with systems knowledge and experience in area such as Linux OS boot sequencing, Kernel, Hypervisor (Xen or KVM), peripheral device development (PCIe or NVMe) and building compute infrastructure to support High Memory and High performance computing workloads. The Nitro High Memory and HPC team owns the purpose built platform development for the High performance computing workloads and database workloads like SAP, Oracle and SQL with tens of terra-byte of memories. Team interfaces directly with system BIOS for bare-metal instances and drives critical system interactions within the Nitro Hypervisor and across EC2 control-plane services. We need engineers with the dive-deep and ownership to work across domains (such as PC peripheral firmware or Linux Kernel internals) to deliver features and new instance types for our customers. Work is typically done in C/C++ or Rust with supporting script and tests in Python and Lua. About the Team Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 10017 BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CA, SANTA CLARA - 165 600.00 USD annually
Date Posted: 2026-05-28 Country: United States of America Location: US-MA-MARLBOROUGH-MA1 1001 Boston Post Rd BLDG 1 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: DoD Clearance: Secret Security Clearance Status: Active and existing security clearance required after day 1 Raytheon Company, Managed by Collins Aerospace Collins Aerospace, an RTX company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio, and expertise to solve customers' toughest challenges and to meet the demands of a rapidly evolving global market. Our Protected Communications Systems (PCS) business, which delivers Resilient National, Strategic, and Tactical Communication Solutions and Integrated C3 Mission Capability Solutions to the US and Allied Nations, is seeking a Senior Digital Electrical Engineer to perform duties at a work center with an emphasis on communications products. The primary work product is the complete digital design of a PCB (Printed Wiring Board) from inception through layout and assembly. The successful candidate must be a self starter and adapt to rapidly changing circumstances, effectively network, and communicate at all levels of the organization to ensure successful completion of projects in support of aggressive schedules. Other desirable attributes include operating with the highest level of personal integrity and be able to work under own initiative, calm under pressure and responsive to change with a logical approach to technical problem resolution and decision making. What You Will Do • Work within a team environment to generate/update Schematics based on Design Requirements • Work with ECAD designers to generate a full Database and Drawings to build PWB/CCAs • Perform Design Analyses (Timing, Power, Signal Integrity) • Perform Design Verification and Troubleshooting • Produce Design Documentation Qualifications You Must Have • Proficient in Schematic Design - Parts selection, Schematic capture, Library management, and Parts Lists creation • Proficient in PCB Design - Stackup/Plane/Routing rules definition & verification, Placement, Constraints setting, and DRC validation • Experience in Artwork (ODB ) validation, reviewing, and approving PWB/CCA drawing sets • Experience in Design Verification/Analysis - Timing, Power, and Signal Integrity Analysis, Bench Level testing, Troubleshooting, and Test Results analysis • Able to generate Design Documentation including Test Requirements & Design Memos • Minimum 5 years of experience as an electrical engineer developing digital/mixed signal high speed Circuit Card Assemblies (CCA) • Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and minimum 5 years prior relevant experience or an Advanced Degree in a related field and minimum 3 years of experience Qualifications We Prefer • Proficiency with Siemen's Xpedition Design Tools is preferred • Knowledgeable of IPC Standards for PCB Design and Fabrication • Knowledgeable of IEEE, MIL standards • Good working knowledge of the Microsoft Suite • Proficiency with analog and mixed signal circuits What We Offer • Medical, dental, and vision insurance • Three weeks of vacation for newly hired employees • Generous 401(k) plan that includes employer matching funds and separate employer retirement contribution, including a Lifetime Income Strategy option • Tuition reimbursement program • Student Loan Repayment Program • Life insurance and disability coverage • Optional coverages you can buy pet insurance, home and auto insurance, additional life and accident insurance, critical illness insurance, group legal, ID theft protection • Birth, adoption, parental leave benefits • Ovia Health, fertility, and family planning • Adoption Assistance • Autism Benefit • Employee Assistance Plan, including up to 10 free counseling sessions • Healthy You Incentives, wellness rewards program • Doctor on Demand, virtual doctor visits • Bright Horizons, child and elder care services • Teladoc Medical Experts, second opinion program • This position is eligible for relocation assistance • And more! Learn More & Apply Now! Do you want to be a part of something bigger? A team whose impact stretches across the world, and even beyond? At Collins Aerospace, our Mission Systems team helps civilian, military and government customers complete their most complex missions - whatever and wherever they may be. Our customers depend on us for intelligent and secure communications, missionized systems for specialized aircraft and spacecraft and collaborative space solutions. By joining our team, you'll have your own critical part to play in ensuring our customer succeeds today while anticipating their needs for tomorrow. Are you up for the challenge? Join our mission today. Please ensure the role type (defined below) is appropriate for your needs before applying to this role. ONSITE: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. At Collins, the paths we pave together lead to limitless possibility. And the bonds we form - with our customers and with each other propel us all higher, again and again. Apply now and be part of the team that's redefining aerospace, every day. Employee Referral Eligible As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
09/13/2026
Full time
Date Posted: 2026-05-28 Country: United States of America Location: US-MA-MARLBOROUGH-MA1 1001 Boston Post Rd BLDG 1 Position Role Type: Onsite U.S. Citizen, U.S. Person, or Immigration Status Requirements: The ability to obtain and maintain a U.S. government issued security clearance is required. U.S. citizenship is required, as only U.S. citizens are eligible for a security clearance Security Clearance Type: DoD Clearance: Secret Security Clearance Status: Active and existing security clearance required after day 1 Raytheon Company, Managed by Collins Aerospace Collins Aerospace, an RTX company, is a leader in technologically advanced and intelligent solutions for the global aerospace and defense industry. Collins Aerospace has the capabilities, comprehensive portfolio, and expertise to solve customers' toughest challenges and to meet the demands of a rapidly evolving global market. Our Protected Communications Systems (PCS) business, which delivers Resilient National, Strategic, and Tactical Communication Solutions and Integrated C3 Mission Capability Solutions to the US and Allied Nations, is seeking a Senior Digital Electrical Engineer to perform duties at a work center with an emphasis on communications products. The primary work product is the complete digital design of a PCB (Printed Wiring Board) from inception through layout and assembly. The successful candidate must be a self starter and adapt to rapidly changing circumstances, effectively network, and communicate at all levels of the organization to ensure successful completion of projects in support of aggressive schedules. Other desirable attributes include operating with the highest level of personal integrity and be able to work under own initiative, calm under pressure and responsive to change with a logical approach to technical problem resolution and decision making. What You Will Do • Work within a team environment to generate/update Schematics based on Design Requirements • Work with ECAD designers to generate a full Database and Drawings to build PWB/CCAs • Perform Design Analyses (Timing, Power, Signal Integrity) • Perform Design Verification and Troubleshooting • Produce Design Documentation Qualifications You Must Have • Proficient in Schematic Design - Parts selection, Schematic capture, Library management, and Parts Lists creation • Proficient in PCB Design - Stackup/Plane/Routing rules definition & verification, Placement, Constraints setting, and DRC validation • Experience in Artwork (ODB ) validation, reviewing, and approving PWB/CCA drawing sets • Experience in Design Verification/Analysis - Timing, Power, and Signal Integrity Analysis, Bench Level testing, Troubleshooting, and Test Results analysis • Able to generate Design Documentation including Test Requirements & Design Memos • Minimum 5 years of experience as an electrical engineer developing digital/mixed signal high speed Circuit Card Assemblies (CCA) • Typically requires a degree in Science, Technology, Engineering or Mathematics (STEM) and minimum 5 years prior relevant experience or an Advanced Degree in a related field and minimum 3 years of experience Qualifications We Prefer • Proficiency with Siemen's Xpedition Design Tools is preferred • Knowledgeable of IPC Standards for PCB Design and Fabrication • Knowledgeable of IEEE, MIL standards • Good working knowledge of the Microsoft Suite • Proficiency with analog and mixed signal circuits What We Offer • Medical, dental, and vision insurance • Three weeks of vacation for newly hired employees • Generous 401(k) plan that includes employer matching funds and separate employer retirement contribution, including a Lifetime Income Strategy option • Tuition reimbursement program • Student Loan Repayment Program • Life insurance and disability coverage • Optional coverages you can buy pet insurance, home and auto insurance, additional life and accident insurance, critical illness insurance, group legal, ID theft protection • Birth, adoption, parental leave benefits • Ovia Health, fertility, and family planning • Adoption Assistance • Autism Benefit • Employee Assistance Plan, including up to 10 free counseling sessions • Healthy You Incentives, wellness rewards program • Doctor on Demand, virtual doctor visits • Bright Horizons, child and elder care services • Teladoc Medical Experts, second opinion program • This position is eligible for relocation assistance • And more! Learn More & Apply Now! Do you want to be a part of something bigger? A team whose impact stretches across the world, and even beyond? At Collins Aerospace, our Mission Systems team helps civilian, military and government customers complete their most complex missions - whatever and wherever they may be. Our customers depend on us for intelligent and secure communications, missionized systems for specialized aircraft and spacecraft and collaborative space solutions. By joining our team, you'll have your own critical part to play in ensuring our customer succeeds today while anticipating their needs for tomorrow. Are you up for the challenge? Join our mission today. Please ensure the role type (defined below) is appropriate for your needs before applying to this role. ONSITE: Employees who are working in Onsite roles will work primarily onsite. This includes all production and maintenance employees, as they are essential to the development of our products. At Collins, the paths we pave together lead to limitless possibility. And the bonds we form - with our customers and with each other propel us all higher, again and again. Apply now and be part of the team that's redefining aerospace, every day. Employee Referral Eligible As part of our commitment to maintaining a secure hiring process, candidates may be asked to attend select steps of the interview process in-person at one of our office locations, regardless of whether the role is designated as on-site, hybrid or remote. The salary range for this role is 86,800 USD - 165,200 USD. The salary range provided is a good faith estimate representative of all experience levels. RTX considers several factors when extending an offer, including but not limited to, the role, function and associated responsibilities, a candidate's work experience, location, education/training, and key skills. Hired applicants may be eligible for benefits, including but not limited to, medical, dental, vision, life insurance, short-term disability, long-term disability, 401(k) match, flexible spending accounts, flexible work schedules, employee assistance program, Employee Scholar Program, parental leave, paid time off, and holidays. Specific benefits are dependent upon the specific business unit as well as whether or not the position is covered by a collective-bargaining agreement. Hired applicants may be eligible for annual short-term and/or long-term incentive compensation programs depending on the level of the position and whether or not it is covered by a collective-bargaining agreement. Payments under these annual programs are not guaranteed and are dependent upon a variety of factors including, but not limited to, individual performance, business unit performance, and/or the company's performance. This role is a U.S.-based role. If the successful candidate resides in a U.S. territory, the appropriate pay structure and benefits will apply. RTX anticipates the application window closing approximately 40 days from the date the notice was posted. However, factors such as candidate flow and business necessity may require RTX to shorten or extend the application window. RTX is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or veteran status, or any other applicable state or federal protected class. RTX provides affirmative action in employment for qualified Individuals with a Disability and Protected Veterans in compliance with Section 503 of the Rehabilitation Act and the Vietnam Era Veterans' Readjustment Assistance Act. Privacy Policy and Terms: Click on this link to read the Policy and Terms
Do you enjoy solving complex problems and driving influential changes? Are you curious about the systems used to run the largest cloud computing infrastructures in the world? Do you thrive in a fast paced and ever-changing environment? If you answered YES to these questions, then our team is looking for you! The AWS Hardware Engineering team drives system innovation in the servers used by all of Amazon Web Services, including EC2, S3, EBS and CloudFront. Our engineers solve the hardest problems that fuse software, hardware, and the cloud. We take big bets on new concepts, enabling AWS services to continue to revolutionize the industry. Optimizing quality, performance, reliability and cost is a massive challenge, and we love it! AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. What you will do: As a Software Development Engineer on the AWS Core Components Manufacturing team, you will design, develop, deploy, and maintain the test automation frameworks and test fixture control software that drive manufacturing test execution for current and next-generation AWS server components across our global ODM/CM sites. You will own the software stack that orchestrates board functional test (BFT), in-circuit test (ICT), and automated test sequencing for unique board variants, including motherboards, PCIe switch/retimer boards, power boards, and system boards, as well as core components, including CPUs and Memory. You will also develop fixture control interfaces for mechanical test stations that validate liquid cooling components, cable assemblies, and thermal hardware at component and rack integration levels. Your test software ensures manufacturing lines can execute tests reliably and repeatably at scale, leading to improved hardware manufacturing yields for AWS servers. Why it matters: Public cloud IT services represent the majority of growth in the overall IT services market and will continue to do so for years to come. The scale of AWS creates a unique opportunity for differentiated hardware that will directly benefit customers. Why you will love it: You will build next-generation software and hardware that powers the cloud. You will deliver improvements for our customers and have a direct impact on our bottom line. You will be part of a growing, fast paced, and fun team. You will have ownership for the implementation of your work. About the team Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Amazon Web Services (AWS) values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Bachelor's degree in Electrical Engineering, Computer Engineering, or a related technical field - 3+ years of experience developing software for manufacturing test environments - 2+ years of experience building automated data pipelines that ingest, process, and report manufacturing test results from ODM/CM production lines PREFERRED QUALIFICATIONS - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Experience building data infrastructure for manufacturing, hardware test, or production operations environments, including ingestion of test results, yield metrics, or quality data from physical systems - Experience with real-time dashboarding, alerting systems, or monitoring platforms that drive operational decision-making - Experience deploying and managing software services across geographically distributed sites - Familiarity with electronics manufacturing processes (SMT, ICT, BFT) or hardware production data flows Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 143 400.00 USD annually
09/13/2026
Full time
Do you enjoy solving complex problems and driving influential changes? Are you curious about the systems used to run the largest cloud computing infrastructures in the world? Do you thrive in a fast paced and ever-changing environment? If you answered YES to these questions, then our team is looking for you! The AWS Hardware Engineering team drives system innovation in the servers used by all of Amazon Web Services, including EC2, S3, EBS and CloudFront. Our engineers solve the hardest problems that fuse software, hardware, and the cloud. We take big bets on new concepts, enabling AWS services to continue to revolutionize the industry. Optimizing quality, performance, reliability and cost is a massive challenge, and we love it! AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we're looking for talented people who want to help. You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion. What you will do: As a Software Development Engineer on the AWS Core Components Manufacturing team, you will design, develop, deploy, and maintain the test automation frameworks and test fixture control software that drive manufacturing test execution for current and next-generation AWS server components across our global ODM/CM sites. You will own the software stack that orchestrates board functional test (BFT), in-circuit test (ICT), and automated test sequencing for unique board variants, including motherboards, PCIe switch/retimer boards, power boards, and system boards, as well as core components, including CPUs and Memory. You will also develop fixture control interfaces for mechanical test stations that validate liquid cooling components, cable assemblies, and thermal hardware at component and rack integration levels. Your test software ensures manufacturing lines can execute tests reliably and repeatably at scale, leading to improved hardware manufacturing yields for AWS servers. Why it matters: Public cloud IT services represent the majority of growth in the overall IT services market and will continue to do so for years to come. The scale of AWS creates a unique opportunity for differentiated hardware that will directly benefit customers. Why you will love it: You will build next-generation software and hardware that powers the cloud. You will deliver improvements for our customers and have a direct impact on our bottom line. You will be part of a growing, fast paced, and fun team. You will have ownership for the implementation of your work. About the team Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Amazon Web Services (AWS) values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Bachelor's degree in Electrical Engineering, Computer Engineering, or a related technical field - 3+ years of experience developing software for manufacturing test environments - 2+ years of experience building automated data pipelines that ingest, process, and report manufacturing test results from ODM/CM production lines PREFERRED QUALIFICATIONS - 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Experience building data infrastructure for manufacturing, hardware test, or production operations environments, including ingestion of test results, yield metrics, or quality data from physical systems - Experience with real-time dashboarding, alerting systems, or monitoring platforms that drive operational decision-making - Experience deploying and managing software services across geographically distributed sites - Familiarity with electronics manufacturing processes (SMT, ICT, BFT) or hardware production data flows Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, WA, Seattle - 143 400.00 USD annually
Amazon Development Center U.S., Inc.
Santa Clara, California
Utility Computing (UC) AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. EC2 Nitro drives the planet's largest, fastest growing and most feature-rich compute cloud. Nitro is AWS's ground-up design for virtualization at global scale built on a fully custom stack of hardware, firmware and applications. Nitro has enabled EC2 to support Intel, AMD and Amazon's custom silicon - Graviton3 - while raising the industry bar for security and performance across our product line. The Nitro Team is looking for engineers with systems knowledge and experience in area such as Linux OS boot sequencing, Kernel, Hypervisor (Xen or KVM), peripheral device development (PCIe or NVMe) and building compute infrastructure to support High Memory and High performance computing workloads. The Nitro High Memory and HPC team owns the purpose built platform development for the High performance computing workloads and database workloads like SAP, Oracle and SQL with tens of terra-byte of memories. Team interfaces directly with system BIOS for bare-metal instances and drives critical system interactions within the Nitro Hypervisor and across EC2 control-plane services. We need engineers with the dive-deep and ownership to work across domains (such as PC peripheral firmware or Linux Kernel internals) to deliver features and new instance types for our customers. Work is typically done in C/C++ or Rust with supporting script and tests in Python and Lua. About the Team Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 10017 BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CA, SANTA CLARA - 165 600.00 USD annually
09/13/2026
Full time
Utility Computing (UC) AWS Utility Computing (UC) provides product innovations - from foundational services such as Amazon's Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. EC2 Nitro drives the planet's largest, fastest growing and most feature-rich compute cloud. Nitro is AWS's ground-up design for virtualization at global scale built on a fully custom stack of hardware, firmware and applications. Nitro has enabled EC2 to support Intel, AMD and Amazon's custom silicon - Graviton3 - while raising the industry bar for security and performance across our product line. The Nitro Team is looking for engineers with systems knowledge and experience in area such as Linux OS boot sequencing, Kernel, Hypervisor (Xen or KVM), peripheral device development (PCIe or NVMe) and building compute infrastructure to support High Memory and High performance computing workloads. The Nitro High Memory and HPC team owns the purpose built platform development for the High performance computing workloads and database workloads like SAP, Oracle and SQL with tens of terra-byte of memories. Team interfaces directly with system BIOS for bare-metal instances and drives critical system interactions within the Nitro Hypervisor and across EC2 control-plane services. We need engineers with the dive-deep and ownership to work across domains (such as PC peripheral firmware or Linux Kernel internals) to deliver features and new instance types for our customers. Work is typically done in C/C++ or Rust with supporting script and tests in Python and Lua. About the Team Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying. About AWS Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud. Mentorship & Career Growth We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 10017 BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . USA, CA, SANTA CLARA - 165 600.00 USD annually
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details
09/13/2026
Full time
McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. The Senior Business Intelligence Analyst is a highly visible, hands-on individual contributor responsible for building and scaling AIM28's analytics, reporting, and value-realization measurement capabilities. Reporting to the AIM28 Finance Lead, this role will design and own end-to-end data models, ETL pipelines, dashboards, and automation solutions that transform complex, fragmented data into trusted insights for executives and program leaders. In addition, this role will support other strategic projects as required. The ideal candidate combines deep technical expertise in SQL, data modeling, BI visualization, automation, and AI-enabled analytics with strong business and finance acumen. Operating as the sole analytics builder within the AIM28 Finance team, this person will create the program's single source of truth for KPI, benefit, investment, and value-realization reporting while driving self-service analytics, reporting automation, and AI-powered insights across the AIM28 portfolio. The Senior Business Intelligence Analyst will lead the development of business intelligence, data visualization, analytics, and reporting automation for the AIM28 program and other strategic projects within U.S. Pharmaceutical Distribution (USPD). AIM28 is McKesson's AI-enabled transformation program, organized around a portfolio of Big Bets, each accountable for delivering measurable business outcomes. This role reports directly into the Sr. Director, Finance (AIM28). This role is the hands-on builder who turns Big Bet data into trusted, automated benefit and value-realization reporting for program leadership and senior executives. The source material varies: some data arrives raw and needs business logic before anyone can use it, some lives in manual files, and some is already visualized in dashboards the business teams built for themselves. You will architect an AI-ready analytics and reporting model that pairs traditional dashboards with AI capabilities such as automated narratives and conversational agents, so stakeholders can self-serve and get to insight faster. Where data is raw, you will establish the transformation logic that makes it consumable. Where reporting lives in manual files or scattered dashboards, you will integrate and standardize it into Big Bet and AIM28 program-level solutions. This is a highly visible individual contributor role. We are looking for a builder with deep SQL proficiency, strong knowledge of data design, and the visualization and storytelling skill to brief senior executives. Expect problems to show up half-defined; your job is to turn them into reliable numbers and clear answers. This role works under the direction of the AIM28 Finance Lead partnering with, Big Bet teams, the transformation office, and McKesson Technology to codify KPI definitions and benefit methodologies into governed data models. The goal is one version of the truth across the program. This is a pure individual-contributor role embedded in Finance, not a role inside a BI or data engineering organization. There is no bench of other BIEs, analytics engineers, or data engineers to hand design, build, or troubleshooting off to, you own the full stack yourself, end to end. Because the role sits in Finance rather than Technology, you should also be comfortable working fluently in financial concepts: ROI, forecasting, variance-to-plan, and business-case logic, gained through direct experience partnering with a business finance or FP&A team. What You'll Do Program & Big Bet reporting Design, build, and maintain the AIM28 program-level and Big Bet-level dashboards that track KPIs, benefits, investments, milestones, and value realization. These dashboards are the single source of truth for program performance. Develop executive-facing reporting for monthly Steering Committee meetings, business reviews, and leadership updates. Translate complex program data into insights leaders can act on. Reporting automation Automate recurring benefit and program reporting end to end. Replace manual, file-based processes with scheduled data flows that are validated and monitored. Find and implement automation opportunities across reporting workflows, including AI capabilities such as automated narratives and summaries that surface insights before anyone asks for them. Data engineering & transformation Build and maintain scalable ETL/ELT pipelines that extract, transform, and clean large, multi-dimensional datasets from multiple sources. These pipelines power the automated Big Bet and AIM28 program-level reporting. Ingest and integrate data from Big Bet teams into harmonized, consumable datasets and data models. Sources include raw operational data, manually maintained files, and dashboards the business built for itself. Establish the business logic that converts raw source data into certified reporting. Document the logic, lineage, and metric definitions well enough that someone else could audit or maintain the work. Design semantic models and curated datasets that people consume today through dashboards and self-service, and that AI agents can consume over time. KPI & benefit frameworks Partner with the AIM28 Finance lead to codify KPI definitions and benefit-realization methodologies into governed data models, so measurement stays consistent across Big Bets. Develop and monitor the KPIs that drive business decisions. Implement data-quality checks, reconciliation, and anomaly detection to protect trust in the numbers. Deep-dive analysis & insights Conduct deep-dive analyses of KPI movements, benefit variances, and program performance questions. Identify root causes and bring conclusions and recommendations to senior leadership. Answer ad hoc analytical questions from program leadership and Big Bet teams. When sources disagree, triangulate across them to validate data fidelity. Self-service & adoption Enable governed self-service analytics for program and Big Bet stakeholders, so fewer questions turn into ad hoc requests or one-off analyses. Own delivery end to end, from requirements and solution design through build, UAT, and adoption. Work with business stakeholders, data engineering, and IT to keep solutions compliant with enterprise data standards. Continuous improvement & influence Prioritize the reporting and automation backlog by business impact and effort. Keep stakeholders current on the roadmap and the trade-offs behind it. Set the standard for analytics practice (data integrity, documentation, versioning) across Big Bet teams, and coach business analysts who build their own reporting. What You Bring A builder's mindset. You take loosely defined problems, work out the business intent behind them, and deliver working solutions end to end: requirements, data model, pipeline, dashboard, adoption. Comfort with ambiguity and imperfect data. Raw extracts, manual spreadsheets, inconsistent definitions, and shifting requirements are the starting point here, not a blocker. Business acumen and financial literacy. You understand core finance concepts, ROI, forecasting, variance-to-plan, business-case logic well enough to hold your own in a finance conversation, not just translate what finance tells you. You have worked directly with a finance or FP&A team before, and you can sit with finance and business partners, understand benefit logic and business cases, and translate between data and business needs. Comfort as a standalone technical IC. This role sits in Finance, not in a BI or data engineering organization. There is no dedicated BIE team, data engineering bench, or technical manager to lean on for design review, code review, or troubleshooting, you are the technical function for AIM28 reporting. You are comfortable being the only builder in the room and owning decisions end to end. A KPI and automation track record. You have developed and monitored KPIs that drive business decisions, and you have built automated reporting systems that replaced manual processes. Executive presence. You have experience communicating and presenting analytical results to senior leadership, in writing and in person. Ownership and judgment. You validate your own outputs, make pragmatic build-versus-reuse trade-offs, and earn trust by being right about the numbers. Organization and prioritization. You manage multiple concurrent workstreams across Big Bets without letting deliverables or timelines slip. Curiosity about AI. You are interested in applying GenAI and agents to reporting, and ideally you have already experimented with them. Technical Skills Expert SQL: complex query development, window functions, and performance tuning on large, multi-dimensional datasets from multiple sources. You write queries that need little post-processing. Data modeling and design: . click apply for full job details
