Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Description The Engineering, Integration and Operations of the Leidos National Security Sector is seeking an energetic Senior Business Development Manager to lead the Business Development (BD) US Navy. The Senior Business Development Manager (BDM) is responsible for all BD activities and strategy development to drive US Navy services support growth. The position will pursue new opportunities in the areas of mission support; systems engineering and integration of C5ISR systems; communications in contested areas; cyber security, cloud, resiliency to support multi-domain and distributed operation in contested environment. Knowledge of Enterprise Resource Planning (ERP) applications or object-oriented analysis and design is required. Experience in Mission Software Networks, Information Technology and/or Digital Transformation is required. BDM will develop and execute the marketing and BD strategy for both accounts. The position will be the creative and trusted agent of the Division Management and Functional Management to drive a culture of innovation and capture excellence. Responsible for the customer call plans. The candidate must thrive in an environment where they are responsible for the management and execution of the full BD life-cycle process across multiple simultaneous pursuits and proposals. In addition to building a qualified pipeline of opportunities, the BDM will help shape customer requirements, translate tacit customer needs into actionable features, drive differentiation in Leidos' solutions and help create a compelling value proposition. The ideal candidate will have previously served as a business development manager and/or capture manager with proven experience supporting DoD customers. Successful candidates will have the ability to conceptualize a vision for winning, to develop strategy and BD capture plans that implement the vision, and, to translate the strategy into win themes. Able to efficiently manage investments in marketing and Bid and Proposal (B&P). The candidate is expected to be a critical partner with the technology team and solution architects and coalesce the division's strategy along with the technology strategy. Primary Responsibilities: Grow the opportunity pipeline, to include existing as well as adjacent markets/customers, through diligent and timely identification/qualification of new business opportunities. Partner with the Leadership to refine the division strategy and shape a balanced portfolio. Lead and participate in the identification, qualification and pursuit of strategic business opportunities, and opportunities greater than $50M in value. Assign and optimize BD and capture resources amongst competing priorities. Drive collaboration across the organization to bring best-in-class solutions to the customer and maximize win probability. Seek and utilize market intelligence and competitor data to position the division for ensuring success. Participate as a thought leader in bid decisions, gate reviews and the development of cost strategies. Conduct customer visits and articulate current and emerging customer needs and requirements. Actively participate in capture activities, to include opportunity gate reviews, black hat sessions, collaboration and workshop sessions, proposal reviews and business case development Drive the development and submission of white papers and RFI responses to proactively shape strategic opportunities. Conduct after-action reviews for all business opportunity capture participants to document lessons learned and identify necessary adjustments to capture technique, strategy, and actions. Develop marketing and B&P budgets and execute BD plans within those approved budgets. Own and conduct monthly detailed pipeline reviews with Senior leadership. Attend tradeshows and execute customer call plans post tradeshows. Basic Qualifications: Requires a BA degree in a technical field and 15+ years of prior relevant experience or Masters with 8+ years of prior relevant experience . 5+ years of BD leadership experience in defense (specifically US Navy), security, or government services Strategic thinker with long term business growth focus Demonstrated successes in leading $25M+ opportunities from identification through proposal submissions Experience managing budgets of $5M+ Demonstrated success in leading and growing DoD services business Ability to identify, establish and use important customer relationships with senior level officials and program stakeholders with DOD Customers Experience developing overall win strategy, shaping deals with customers, developing team strategies, understanding pricing and assisting in developing winning price Knowledge of competitors and ability to model competitor behaviors in the market Ability to identify key growth areas and develop new business aligned with the company's growth strategy Proven ability to collaborate within and across organizational boundaries Knowledge of Government contracting and current acquisition trends and customer buying behaviors Excellent written and oral communication skills; experience presenting to senior executives, peers, and customers A technical degree is required. Ability to empower and engage people and instill drive and passion into the organization Secret level clearance required, TS preferred Preferred Qualifications: 5 + years of BD leadership experience in mission-critical solutions in areas such as logistics, product support and modernization, and mission operations 5+ years of program management Management of a qualified pipeline of opportunities with a value of $2B+ Original Posting Date: 2024-04-05 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $144,300.00 - $260,850.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
04/19/2024
Full time
Description The Engineering, Integration and Operations of the Leidos National Security Sector is seeking an energetic Senior Business Development Manager to lead the Business Development (BD) US Navy. The Senior Business Development Manager (BDM) is responsible for all BD activities and strategy development to drive US Navy services support growth. The position will pursue new opportunities in the areas of mission support; systems engineering and integration of C5ISR systems; communications in contested areas; cyber security, cloud, resiliency to support multi-domain and distributed operation in contested environment. Knowledge of Enterprise Resource Planning (ERP) applications or object-oriented analysis and design is required. Experience in Mission Software Networks, Information Technology and/or Digital Transformation is required. BDM will develop and execute the marketing and BD strategy for both accounts. The position will be the creative and trusted agent of the Division Management and Functional Management to drive a culture of innovation and capture excellence. Responsible for the customer call plans. The candidate must thrive in an environment where they are responsible for the management and execution of the full BD life-cycle process across multiple simultaneous pursuits and proposals. In addition to building a qualified pipeline of opportunities, the BDM will help shape customer requirements, translate tacit customer needs into actionable features, drive differentiation in Leidos' solutions and help create a compelling value proposition. The ideal candidate will have previously served as a business development manager and/or capture manager with proven experience supporting DoD customers. Successful candidates will have the ability to conceptualize a vision for winning, to develop strategy and BD capture plans that implement the vision, and, to translate the strategy into win themes. Able to efficiently manage investments in marketing and Bid and Proposal (B&P). The candidate is expected to be a critical partner with the technology team and solution architects and coalesce the division's strategy along with the technology strategy. Primary Responsibilities: Grow the opportunity pipeline, to include existing as well as adjacent markets/customers, through diligent and timely identification/qualification of new business opportunities. Partner with the Leadership to refine the division strategy and shape a balanced portfolio. Lead and participate in the identification, qualification and pursuit of strategic business opportunities, and opportunities greater than $50M in value. Assign and optimize BD and capture resources amongst competing priorities. Drive collaboration across the organization to bring best-in-class solutions to the customer and maximize win probability. Seek and utilize market intelligence and competitor data to position the division for ensuring success. Participate as a thought leader in bid decisions, gate reviews and the development of cost strategies. Conduct customer visits and articulate current and emerging customer needs and requirements. Actively participate in capture activities, to include opportunity gate reviews, black hat sessions, collaboration and workshop sessions, proposal reviews and business case development Drive the development and submission of white papers and RFI responses to proactively shape strategic opportunities. Conduct after-action reviews for all business opportunity capture participants to document lessons learned and identify necessary adjustments to capture technique, strategy, and actions. Develop marketing and B&P budgets and execute BD plans within those approved budgets. Own and conduct monthly detailed pipeline reviews with Senior leadership. Attend tradeshows and execute customer call plans post tradeshows. Basic Qualifications: Requires a BA degree in a technical field and 15+ years of prior relevant experience or Masters with 8+ years of prior relevant experience . 5+ years of BD leadership experience in defense (specifically US Navy), security, or government services Strategic thinker with long term business growth focus Demonstrated successes in leading $25M+ opportunities from identification through proposal submissions Experience managing budgets of $5M+ Demonstrated success in leading and growing DoD services business Ability to identify, establish and use important customer relationships with senior level officials and program stakeholders with DOD Customers Experience developing overall win strategy, shaping deals with customers, developing team strategies, understanding pricing and assisting in developing winning price Knowledge of competitors and ability to model competitor behaviors in the market Ability to identify key growth areas and develop new business aligned with the company's growth strategy Proven ability to collaborate within and across organizational boundaries Knowledge of Government contracting and current acquisition trends and customer buying behaviors Excellent written and oral communication skills; experience presenting to senior executives, peers, and customers A technical degree is required. Ability to empower and engage people and instill drive and passion into the organization Secret level clearance required, TS preferred Preferred Qualifications: 5 + years of BD leadership experience in mission-critical solutions in areas such as logistics, product support and modernization, and mission operations 5+ years of program management Management of a qualified pipeline of opportunities with a value of $2B+ Original Posting Date: 2024-04-05 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $144,300.00 - $260,850.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Description The Engineering, Integration and Operations of the Leidos National Security Sector is seeking an energetic Senior Business Development Manager to lead the Business Development (BD) US Navy. The Senior Business Development Manager (BDM) is responsible for all BD activities and strategy development to drive US Navy services support growth. The position will pursue new opportunities in the areas of mission support; systems engineering and integration of C5ISR systems; communications in contested areas; cyber security, cloud, resiliency to support multi-domain and distributed operation in contested environment. Knowledge of Enterprise Resource Planning (ERP) applications or object-oriented analysis and design is required. Experience in Mission Software Networks, Information Technology and/or Digital Transformation is required. BDM will develop and execute the marketing and BD strategy for both accounts. The position will be the creative and trusted agent of the Division Management and Functional Management to drive a culture of innovation and capture excellence. Responsible for the customer call plans. The candidate must thrive in an environment where they are responsible for the management and execution of the full BD life-cycle process across multiple simultaneous pursuits and proposals. In addition to building a qualified pipeline of opportunities, the BDM will help shape customer requirements, translate tacit customer needs into actionable features, drive differentiation in Leidos' solutions and help create a compelling value proposition. The ideal candidate will have previously served as a business development manager and/or capture manager with proven experience supporting DoD customers. Successful candidates will have the ability to conceptualize a vision for winning, to develop strategy and BD capture plans that implement the vision, and, to translate the strategy into win themes. Able to efficiently manage investments in marketing and Bid and Proposal (B&P). The candidate is expected to be a critical partner with the technology team and solution architects and coalesce the division's strategy along with the technology strategy. Primary Responsibilities: Grow the opportunity pipeline, to include existing as well as adjacent markets/customers, through diligent and timely identification/qualification of new business opportunities. Partner with the Leadership to refine the division strategy and shape a balanced portfolio. Lead and participate in the identification, qualification and pursuit of strategic business opportunities, and opportunities greater than $50M in value. Assign and optimize BD and capture resources amongst competing priorities. Drive collaboration across the organization to bring best-in-class solutions to the customer and maximize win probability. Seek and utilize market intelligence and competitor data to position the division for ensuring success. Participate as a thought leader in bid decisions, gate reviews and the development of cost strategies. Conduct customer visits and articulate current and emerging customer needs and requirements. Actively participate in capture activities, to include opportunity gate reviews, black hat sessions, collaboration and workshop sessions, proposal reviews and business case development Drive the development and submission of white papers and RFI responses to proactively shape strategic opportunities. Conduct after-action reviews for all business opportunity capture participants to document lessons learned and identify necessary adjustments to capture technique, strategy, and actions. Develop marketing and B&P budgets and execute BD plans within those approved budgets. Own and conduct monthly detailed pipeline reviews with Senior leadership. Attend tradeshows and execute customer call plans post tradeshows. Basic Qualifications: Requires a BA degree in a technical field and 15+ years of prior relevant experience or Masters with 8+ years of prior relevant experience . 5+ years of BD leadership experience in defense (specifically US Navy), security, or government services Strategic thinker with long term business growth focus Demonstrated successes in leading $25M+ opportunities from identification through proposal submissions Experience managing budgets of $5M+ Demonstrated success in leading and growing DoD services business Ability to identify, establish and use important customer relationships with senior level officials and program stakeholders with DOD Customers Experience developing overall win strategy, shaping deals with customers, developing team strategies, understanding pricing and assisting in developing winning price Knowledge of competitors and ability to model competitor behaviors in the market Ability to identify key growth areas and develop new business aligned with the company's growth strategy Proven ability to collaborate within and across organizational boundaries Knowledge of Government contracting and current acquisition trends and customer buying behaviors Excellent written and oral communication skills; experience presenting to senior executives, peers, and customers A technical degree is required. Ability to empower and engage people and instill drive and passion into the organization Secret level clearance required, TS preferred Preferred Qualifications: 5 + years of BD leadership experience in mission-critical solutions in areas such as logistics, product support and modernization, and mission operations 5+ years of program management Management of a qualified pipeline of opportunities with a value of $2B+ Original Posting Date: 2024-04-05 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $144,300.00 - $260,850.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
04/19/2024
Full time
Description The Engineering, Integration and Operations of the Leidos National Security Sector is seeking an energetic Senior Business Development Manager to lead the Business Development (BD) US Navy. The Senior Business Development Manager (BDM) is responsible for all BD activities and strategy development to drive US Navy services support growth. The position will pursue new opportunities in the areas of mission support; systems engineering and integration of C5ISR systems; communications in contested areas; cyber security, cloud, resiliency to support multi-domain and distributed operation in contested environment. Knowledge of Enterprise Resource Planning (ERP) applications or object-oriented analysis and design is required. Experience in Mission Software Networks, Information Technology and/or Digital Transformation is required. BDM will develop and execute the marketing and BD strategy for both accounts. The position will be the creative and trusted agent of the Division Management and Functional Management to drive a culture of innovation and capture excellence. Responsible for the customer call plans. The candidate must thrive in an environment where they are responsible for the management and execution of the full BD life-cycle process across multiple simultaneous pursuits and proposals. In addition to building a qualified pipeline of opportunities, the BDM will help shape customer requirements, translate tacit customer needs into actionable features, drive differentiation in Leidos' solutions and help create a compelling value proposition. The ideal candidate will have previously served as a business development manager and/or capture manager with proven experience supporting DoD customers. Successful candidates will have the ability to conceptualize a vision for winning, to develop strategy and BD capture plans that implement the vision, and, to translate the strategy into win themes. Able to efficiently manage investments in marketing and Bid and Proposal (B&P). The candidate is expected to be a critical partner with the technology team and solution architects and coalesce the division's strategy along with the technology strategy. Primary Responsibilities: Grow the opportunity pipeline, to include existing as well as adjacent markets/customers, through diligent and timely identification/qualification of new business opportunities. Partner with the Leadership to refine the division strategy and shape a balanced portfolio. Lead and participate in the identification, qualification and pursuit of strategic business opportunities, and opportunities greater than $50M in value. Assign and optimize BD and capture resources amongst competing priorities. Drive collaboration across the organization to bring best-in-class solutions to the customer and maximize win probability. Seek and utilize market intelligence and competitor data to position the division for ensuring success. Participate as a thought leader in bid decisions, gate reviews and the development of cost strategies. Conduct customer visits and articulate current and emerging customer needs and requirements. Actively participate in capture activities, to include opportunity gate reviews, black hat sessions, collaboration and workshop sessions, proposal reviews and business case development Drive the development and submission of white papers and RFI responses to proactively shape strategic opportunities. Conduct after-action reviews for all business opportunity capture participants to document lessons learned and identify necessary adjustments to capture technique, strategy, and actions. Develop marketing and B&P budgets and execute BD plans within those approved budgets. Own and conduct monthly detailed pipeline reviews with Senior leadership. Attend tradeshows and execute customer call plans post tradeshows. Basic Qualifications: Requires a BA degree in a technical field and 15+ years of prior relevant experience or Masters with 8+ years of prior relevant experience . 5+ years of BD leadership experience in defense (specifically US Navy), security, or government services Strategic thinker with long term business growth focus Demonstrated successes in leading $25M+ opportunities from identification through proposal submissions Experience managing budgets of $5M+ Demonstrated success in leading and growing DoD services business Ability to identify, establish and use important customer relationships with senior level officials and program stakeholders with DOD Customers Experience developing overall win strategy, shaping deals with customers, developing team strategies, understanding pricing and assisting in developing winning price Knowledge of competitors and ability to model competitor behaviors in the market Ability to identify key growth areas and develop new business aligned with the company's growth strategy Proven ability to collaborate within and across organizational boundaries Knowledge of Government contracting and current acquisition trends and customer buying behaviors Excellent written and oral communication skills; experience presenting to senior executives, peers, and customers A technical degree is required. Ability to empower and engage people and instill drive and passion into the organization Secret level clearance required, TS preferred Preferred Qualifications: 5 + years of BD leadership experience in mission-critical solutions in areas such as logistics, product support and modernization, and mission operations 5+ years of program management Management of a qualified pipeline of opportunities with a value of $2B+ Original Posting Date: 2024-04-05 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $144,300.00 - $260,850.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Center 3 (19075), United States of America, McLean, Virginia Director, Risk Lead for Generative AI We are growing! The Enterprise Services Business Risk Office provides risk management support to several lines of business including: Tech, Digital, Brand, Enterprise Supplier Management, Capital One Ventures, External Affairs, Capital One Software (COS) and Enterprise AI/ML. We are on the cutting edge of risk management and provide support for new and emerging technologies as well as critical business strategies. Capital One has taken a bold journey to build a technology company, while operating in a complex, highly regulated business. Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. As an AI/ML risk leader, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build in a well managed way. As a Director Risk Leader supporting the AI Foundations Program, you will partner with colleagues across AI product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One's continued stability and success. Responsibilities require partnering with a broad set of leaders and stakeholders to identify existing and potential emerging risks in an open, collaborative environment where new ideas and solutions are both welcomed and rewarded. The successful candidate will have knowledge of AI/ML product development processes including an understanding of the model development lifecycle with a lens towards building and scaling AI technologies in a responsible and well managed manner. The candidate will possess an understanding of process management strategies, risk methodologies and have the ability to build relationships with business and risk partners. Core responsibilities include oversight of process hierarchy, critical business process identification and consultation, horizontal support for Enterprise Services controls program, and controls development of internal solutions uniquely designed to meet the challenges of a digital-first, cloud-first business at scale. Leads other associates, when necessary, and ensures best practices executed by the team and shared broadly across the Enterprise. Responsibilities of the Director, Gen AI Risk Guide include and are not limited to: Develop and implement processes to provide independent analysis and effective plans to mitigate risk related to the company's AI/ML management practices. Ensure effective governance by identifying, framing, and presenting risk topics to be discussed by senior management in enterprise risk forums. Advise and consult on the development and management of new Generative AI policies, standards and procedures. Stay current on emerging risk and potential implications to the company as related to accountable domain(s). Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives. Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups. Analyzes data and influences others to proactively identify risks and trends. Balances multiple priorities to help drive business value and support team objectives, while managing tasks and activities related to risk management initiatives Here's what we're looking for in an ideal teammate: You are a critical thinker who seeks to understand the business and its control environment. You possess a relentless focus on quality and timeliness. You adapt to change, embrace bold ideas, and are intellectually curious. You like to ask questions, test assumptions, and challenge conventional thinking. You develop influential relationships based upon shared risk objectives and trust to deliver outstanding business impact. You're a teacher. You do the right thing and lead by example. You have a passion for coaching and investing in the betterment of your team. You lead through change with candor and optimism. You create energy and an environment that fosters trust, collaboration, and belonging, making it easy to attract, hire, and retain top talent. Basic Qualifications: Bachelor's degree or military experience At least 5 years of experience in Process, Project, Risk Management, or Cloud Risk Management At least 3 years direct experience with AI/ML model lifecycle management or operations or deployments Preferred Qualifications: Master's Degree in Computer Science or in an Engineering discipline At least 6 years of experience in Process, Project, Product, Risk Management, or Cloud Risk Management (or equivalent) At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices At least 4 years leading a team Effectively work in white space and bring structure to deliver on our well managed agenda Experience drafting and communicating reports or analytic assessments for executives Ability to communicate clearly and to interact effectively at all levels of the organization, and to influence as warranted and appropriate to drive consensus Experience with identifying and communicating key risks to AI implementations and architectures Experience with risk analysis and reports that describe risk implications to executives Ability to manage multiple high-visibility and high-impact projects while maintaining superior results Familiarity with AI/ML frameworks (NIST AI) Prior experience working in financial services or other highly regulated sectors Experience with security best practices for generative AI development and deployments At this time, Capital One will not sponsor a new 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. New York City (Hybrid On-Site): $233,100 - $266,000 for Director, Cyber Risk & Analysis 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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 . click apply for full job details
04/19/2024
Full time
Center 3 (19075), United States of America, McLean, Virginia Director, Risk Lead for Generative AI We are growing! The Enterprise Services Business Risk Office provides risk management support to several lines of business including: Tech, Digital, Brand, Enterprise Supplier Management, Capital One Ventures, External Affairs, Capital One Software (COS) and Enterprise AI/ML. We are on the cutting edge of risk management and provide support for new and emerging technologies as well as critical business strategies. Capital One has taken a bold journey to build a technology company, while operating in a complex, highly regulated business. Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. As an AI/ML risk leader, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build in a well managed way. As a Director Risk Leader supporting the AI Foundations Program, you will partner with colleagues across AI product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One's continued stability and success. Responsibilities require partnering with a broad set of leaders and stakeholders to identify existing and potential emerging risks in an open, collaborative environment where new ideas and solutions are both welcomed and rewarded. The successful candidate will have knowledge of AI/ML product development processes including an understanding of the model development lifecycle with a lens towards building and scaling AI technologies in a responsible and well managed manner. The candidate will possess an understanding of process management strategies, risk methodologies and have the ability to build relationships with business and risk partners. Core responsibilities include oversight of process hierarchy, critical business process identification and consultation, horizontal support for Enterprise Services controls program, and controls development of internal solutions uniquely designed to meet the challenges of a digital-first, cloud-first business at scale. Leads other associates, when necessary, and ensures best practices executed by the team and shared broadly across the Enterprise. Responsibilities of the Director, Gen AI Risk Guide include and are not limited to: Develop and implement processes to provide independent analysis and effective plans to mitigate risk related to the company's AI/ML management practices. Ensure effective governance by identifying, framing, and presenting risk topics to be discussed by senior management in enterprise risk forums. Advise and consult on the development and management of new Generative AI policies, standards and procedures. Stay current on emerging risk and potential implications to the company as related to accountable domain(s). Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives. Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups. Analyzes data and influences others to proactively identify risks and trends. Balances multiple priorities to help drive business value and support team objectives, while managing tasks and activities related to risk management initiatives Here's what we're looking for in an ideal teammate: You are a critical thinker who seeks to understand the business and its control environment. You possess a relentless focus on quality and timeliness. You adapt to change, embrace bold ideas, and are intellectually curious. You like to ask questions, test assumptions, and challenge conventional thinking. You develop influential relationships based upon shared risk objectives and trust to deliver outstanding business impact. You're a teacher. You do the right thing and lead by example. You have a passion for coaching and investing in the betterment of your team. You lead through change with candor and optimism. You create energy and an environment that fosters trust, collaboration, and belonging, making it easy to attract, hire, and retain top talent. Basic Qualifications: Bachelor's degree or military experience At least 5 years of experience in Process, Project, Risk Management, or Cloud Risk Management At least 3 years direct experience with AI/ML model lifecycle management or operations or deployments Preferred Qualifications: Master's Degree in Computer Science or in an Engineering discipline At least 6 years of experience in Process, Project, Product, Risk Management, or Cloud Risk Management (or equivalent) At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices At least 4 years leading a team Effectively work in white space and bring structure to deliver on our well managed agenda Experience drafting and communicating reports or analytic assessments for executives Ability to communicate clearly and to interact effectively at all levels of the organization, and to influence as warranted and appropriate to drive consensus Experience with identifying and communicating key risks to AI implementations and architectures Experience with risk analysis and reports that describe risk implications to executives Ability to manage multiple high-visibility and high-impact projects while maintaining superior results Familiarity with AI/ML frameworks (NIST AI) Prior experience working in financial services or other highly regulated sectors Experience with security best practices for generative AI development and deployments At this time, Capital One will not sponsor a new 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. New York City (Hybrid On-Site): $233,100 - $266,000 for Director, Cyber Risk & Analysis 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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 . click apply for full job details
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: NY - New York, United States of America, New York, New York Distinguished Engineer, Generative AI Systems (Remote-Eligible) Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building distributed computing HPC and large-scale ML systems At least 5 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $274,800 - $313,600 for Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $291,100 - $332,300 for Distinguished Machine Learning Engineer Remote (Regardless of Location): $232,900 - $265,800 for Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Description The Engineering, Integration and Operations of the Leidos National Security Sector is seeking an energetic Senior Business Development Manager to lead the Business Development (BD) US Navy. The Senior Business Development Manager (BDM) is responsible for all BD activities and strategy development to drive US Navy services support growth. The position will pursue new opportunities in the areas of mission support; systems engineering and integration of C5ISR systems; communications in contested areas; cyber security, cloud, resiliency to support multi-domain and distributed operation in contested environment. Knowledge of Enterprise Resource Planning (ERP) applications or object-oriented analysis and design is required. Experience in Mission Software Networks, Information Technology and/or Digital Transformation is required. BDM will develop and execute the marketing and BD strategy for both accounts. The position will be the creative and trusted agent of the Division Management and Functional Management to drive a culture of innovation and capture excellence. Responsible for the customer call plans. The candidate must thrive in an environment where they are responsible for the management and execution of the full BD life-cycle process across multiple simultaneous pursuits and proposals. In addition to building a qualified pipeline of opportunities, the BDM will help shape customer requirements, translate tacit customer needs into actionable features, drive differentiation in Leidos' solutions and help create a compelling value proposition. The ideal candidate will have previously served as a business development manager and/or capture manager with proven experience supporting DoD customers. Successful candidates will have the ability to conceptualize a vision for winning, to develop strategy and BD capture plans that implement the vision, and, to translate the strategy into win themes. Able to efficiently manage investments in marketing and Bid and Proposal (B&P). The candidate is expected to be a critical partner with the technology team and solution architects and coalesce the division's strategy along with the technology strategy. Primary Responsibilities: Grow the opportunity pipeline, to include existing as well as adjacent markets/customers, through diligent and timely identification/qualification of new business opportunities. Partner with the Leadership to refine the division strategy and shape a balanced portfolio. Lead and participate in the identification, qualification and pursuit of strategic business opportunities, and opportunities greater than $50M in value. Assign and optimize BD and capture resources amongst competing priorities. Drive collaboration across the organization to bring best-in-class solutions to the customer and maximize win probability. Seek and utilize market intelligence and competitor data to position the division for ensuring success. Participate as a thought leader in bid decisions, gate reviews and the development of cost strategies. Conduct customer visits and articulate current and emerging customer needs and requirements. Actively participate in capture activities, to include opportunity gate reviews, black hat sessions, collaboration and workshop sessions, proposal reviews and business case development Drive the development and submission of white papers and RFI responses to proactively shape strategic opportunities. Conduct after-action reviews for all business opportunity capture participants to document lessons learned and identify necessary adjustments to capture technique, strategy, and actions. Develop marketing and B&P budgets and execute BD plans within those approved budgets. Own and conduct monthly detailed pipeline reviews with Senior leadership. Attend tradeshows and execute customer call plans post tradeshows. Basic Qualifications: Requires a BA degree in a technical field and 15+ years of prior relevant experience or Masters with 8+ years of prior relevant experience . 5+ years of BD leadership experience in defense (specifically US Navy), security, or government services Strategic thinker with long term business growth focus Demonstrated successes in leading $25M+ opportunities from identification through proposal submissions Experience managing budgets of $5M+ Demonstrated success in leading and growing DoD services business Ability to identify, establish and use important customer relationships with senior level officials and program stakeholders with DOD Customers Experience developing overall win strategy, shaping deals with customers, developing team strategies, understanding pricing and assisting in developing winning price Knowledge of competitors and ability to model competitor behaviors in the market Ability to identify key growth areas and develop new business aligned with the company's growth strategy Proven ability to collaborate within and across organizational boundaries Knowledge of Government contracting and current acquisition trends and customer buying behaviors Excellent written and oral communication skills; experience presenting to senior executives, peers, and customers A technical degree is required. Ability to empower and engage people and instill drive and passion into the organization Secret level clearance required, TS preferred Preferred Qualifications: 5 + years of BD leadership experience in mission-critical solutions in areas such as logistics, product support and modernization, and mission operations 5+ years of program management Management of a qualified pipeline of opportunities with a value of $2B+ Original Posting Date: 2024-04-05 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $144,300.00 - $260,850.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
04/19/2024
Full time
Description The Engineering, Integration and Operations of the Leidos National Security Sector is seeking an energetic Senior Business Development Manager to lead the Business Development (BD) US Navy. The Senior Business Development Manager (BDM) is responsible for all BD activities and strategy development to drive US Navy services support growth. The position will pursue new opportunities in the areas of mission support; systems engineering and integration of C5ISR systems; communications in contested areas; cyber security, cloud, resiliency to support multi-domain and distributed operation in contested environment. Knowledge of Enterprise Resource Planning (ERP) applications or object-oriented analysis and design is required. Experience in Mission Software Networks, Information Technology and/or Digital Transformation is required. BDM will develop and execute the marketing and BD strategy for both accounts. The position will be the creative and trusted agent of the Division Management and Functional Management to drive a culture of innovation and capture excellence. Responsible for the customer call plans. The candidate must thrive in an environment where they are responsible for the management and execution of the full BD life-cycle process across multiple simultaneous pursuits and proposals. In addition to building a qualified pipeline of opportunities, the BDM will help shape customer requirements, translate tacit customer needs into actionable features, drive differentiation in Leidos' solutions and help create a compelling value proposition. The ideal candidate will have previously served as a business development manager and/or capture manager with proven experience supporting DoD customers. Successful candidates will have the ability to conceptualize a vision for winning, to develop strategy and BD capture plans that implement the vision, and, to translate the strategy into win themes. Able to efficiently manage investments in marketing and Bid and Proposal (B&P). The candidate is expected to be a critical partner with the technology team and solution architects and coalesce the division's strategy along with the technology strategy. Primary Responsibilities: Grow the opportunity pipeline, to include existing as well as adjacent markets/customers, through diligent and timely identification/qualification of new business opportunities. Partner with the Leadership to refine the division strategy and shape a balanced portfolio. Lead and participate in the identification, qualification and pursuit of strategic business opportunities, and opportunities greater than $50M in value. Assign and optimize BD and capture resources amongst competing priorities. Drive collaboration across the organization to bring best-in-class solutions to the customer and maximize win probability. Seek and utilize market intelligence and competitor data to position the division for ensuring success. Participate as a thought leader in bid decisions, gate reviews and the development of cost strategies. Conduct customer visits and articulate current and emerging customer needs and requirements. Actively participate in capture activities, to include opportunity gate reviews, black hat sessions, collaboration and workshop sessions, proposal reviews and business case development Drive the development and submission of white papers and RFI responses to proactively shape strategic opportunities. Conduct after-action reviews for all business opportunity capture participants to document lessons learned and identify necessary adjustments to capture technique, strategy, and actions. Develop marketing and B&P budgets and execute BD plans within those approved budgets. Own and conduct monthly detailed pipeline reviews with Senior leadership. Attend tradeshows and execute customer call plans post tradeshows. Basic Qualifications: Requires a BA degree in a technical field and 15+ years of prior relevant experience or Masters with 8+ years of prior relevant experience . 5+ years of BD leadership experience in defense (specifically US Navy), security, or government services Strategic thinker with long term business growth focus Demonstrated successes in leading $25M+ opportunities from identification through proposal submissions Experience managing budgets of $5M+ Demonstrated success in leading and growing DoD services business Ability to identify, establish and use important customer relationships with senior level officials and program stakeholders with DOD Customers Experience developing overall win strategy, shaping deals with customers, developing team strategies, understanding pricing and assisting in developing winning price Knowledge of competitors and ability to model competitor behaviors in the market Ability to identify key growth areas and develop new business aligned with the company's growth strategy Proven ability to collaborate within and across organizational boundaries Knowledge of Government contracting and current acquisition trends and customer buying behaviors Excellent written and oral communication skills; experience presenting to senior executives, peers, and customers A technical degree is required. Ability to empower and engage people and instill drive and passion into the organization Secret level clearance required, TS preferred Preferred Qualifications: 5 + years of BD leadership experience in mission-critical solutions in areas such as logistics, product support and modernization, and mission operations 5+ years of program management Management of a qualified pipeline of opportunities with a value of $2B+ Original Posting Date: 2024-04-05 While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $144,300.00 - $260,850.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Center 3 (19075), United States of America, McLean, Virginia Director, Risk Lead for Generative AI We are growing! The Enterprise Services Business Risk Office provides risk management support to several lines of business including: Tech, Digital, Brand, Enterprise Supplier Management, Capital One Ventures, External Affairs, Capital One Software (COS) and Enterprise AI/ML. We are on the cutting edge of risk management and provide support for new and emerging technologies as well as critical business strategies. Capital One has taken a bold journey to build a technology company, while operating in a complex, highly regulated business. Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. As an AI/ML risk leader, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build in a well managed way. As a Director Risk Leader supporting the AI Foundations Program, you will partner with colleagues across AI product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One's continued stability and success. Responsibilities require partnering with a broad set of leaders and stakeholders to identify existing and potential emerging risks in an open, collaborative environment where new ideas and solutions are both welcomed and rewarded. The successful candidate will have knowledge of AI/ML product development processes including an understanding of the model development lifecycle with a lens towards building and scaling AI technologies in a responsible and well managed manner. The candidate will possess an understanding of process management strategies, risk methodologies and have the ability to build relationships with business and risk partners. Core responsibilities include oversight of process hierarchy, critical business process identification and consultation, horizontal support for Enterprise Services controls program, and controls development of internal solutions uniquely designed to meet the challenges of a digital-first, cloud-first business at scale. Leads other associates, when necessary, and ensures best practices executed by the team and shared broadly across the Enterprise. Responsibilities of the Director, Gen AI Risk Guide include and are not limited to: Develop and implement processes to provide independent analysis and effective plans to mitigate risk related to the company's AI/ML management practices. Ensure effective governance by identifying, framing, and presenting risk topics to be discussed by senior management in enterprise risk forums. Advise and consult on the development and management of new Generative AI policies, standards and procedures. Stay current on emerging risk and potential implications to the company as related to accountable domain(s). Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives. Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups. Analyzes data and influences others to proactively identify risks and trends. Balances multiple priorities to help drive business value and support team objectives, while managing tasks and activities related to risk management initiatives Here's what we're looking for in an ideal teammate: You are a critical thinker who seeks to understand the business and its control environment. You possess a relentless focus on quality and timeliness. You adapt to change, embrace bold ideas, and are intellectually curious. You like to ask questions, test assumptions, and challenge conventional thinking. You develop influential relationships based upon shared risk objectives and trust to deliver outstanding business impact. You're a teacher. You do the right thing and lead by example. You have a passion for coaching and investing in the betterment of your team. You lead through change with candor and optimism. You create energy and an environment that fosters trust, collaboration, and belonging, making it easy to attract, hire, and retain top talent. Basic Qualifications: Bachelor's degree or military experience At least 5 years of experience in Process, Project, Risk Management, or Cloud Risk Management At least 3 years direct experience with AI/ML model lifecycle management or operations or deployments Preferred Qualifications: Master's Degree in Computer Science or in an Engineering discipline At least 6 years of experience in Process, Project, Product, Risk Management, or Cloud Risk Management (or equivalent) At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices At least 4 years leading a team Effectively work in white space and bring structure to deliver on our well managed agenda Experience drafting and communicating reports or analytic assessments for executives Ability to communicate clearly and to interact effectively at all levels of the organization, and to influence as warranted and appropriate to drive consensus Experience with identifying and communicating key risks to AI implementations and architectures Experience with risk analysis and reports that describe risk implications to executives Ability to manage multiple high-visibility and high-impact projects while maintaining superior results Familiarity with AI/ML frameworks (NIST AI) Prior experience working in financial services or other highly regulated sectors Experience with security best practices for generative AI development and deployments At this time, Capital One will not sponsor a new 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. New York City (Hybrid On-Site): $233,100 - $266,000 for Director, Cyber Risk & Analysis 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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 . click apply for full job details
04/19/2024
Full time
Center 3 (19075), United States of America, McLean, Virginia Director, Risk Lead for Generative AI We are growing! The Enterprise Services Business Risk Office provides risk management support to several lines of business including: Tech, Digital, Brand, Enterprise Supplier Management, Capital One Ventures, External Affairs, Capital One Software (COS) and Enterprise AI/ML. We are on the cutting edge of risk management and provide support for new and emerging technologies as well as critical business strategies. Capital One has taken a bold journey to build a technology company, while operating in a complex, highly regulated business. Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of generative AI that few other organizations can. We are committed to building world-class applied science and platform engineering teams and continue our industry leading capabilities with breakthrough product experiences and scalable, high-performance generative AI infrastructure. As an AI/ML risk leader, you will help bring the transformative power of generative AI to reimagine how we serve our customers and businesses who have come to love the products and services we build in a well managed way. As a Director Risk Leader supporting the AI Foundations Program, you will partner with colleagues across AI product, design and tech to deliver results that have a direct impact on customer experience and implement risk solutions to ensure Capital One's continued stability and success. Responsibilities require partnering with a broad set of leaders and stakeholders to identify existing and potential emerging risks in an open, collaborative environment where new ideas and solutions are both welcomed and rewarded. The successful candidate will have knowledge of AI/ML product development processes including an understanding of the model development lifecycle with a lens towards building and scaling AI technologies in a responsible and well managed manner. The candidate will possess an understanding of process management strategies, risk methodologies and have the ability to build relationships with business and risk partners. Core responsibilities include oversight of process hierarchy, critical business process identification and consultation, horizontal support for Enterprise Services controls program, and controls development of internal solutions uniquely designed to meet the challenges of a digital-first, cloud-first business at scale. Leads other associates, when necessary, and ensures best practices executed by the team and shared broadly across the Enterprise. Responsibilities of the Director, Gen AI Risk Guide include and are not limited to: Develop and implement processes to provide independent analysis and effective plans to mitigate risk related to the company's AI/ML management practices. Ensure effective governance by identifying, framing, and presenting risk topics to be discussed by senior management in enterprise risk forums. Advise and consult on the development and management of new Generative AI policies, standards and procedures. Stay current on emerging risk and potential implications to the company as related to accountable domain(s). Collaborate effectively with colleagues, stakeholders, and leaders across multiple organizations to achieve strategic objectives. Coordinate program-related activities and deliverables to ensure effective collaboration within the team and across stakeholder groups. Analyzes data and influences others to proactively identify risks and trends. Balances multiple priorities to help drive business value and support team objectives, while managing tasks and activities related to risk management initiatives Here's what we're looking for in an ideal teammate: You are a critical thinker who seeks to understand the business and its control environment. You possess a relentless focus on quality and timeliness. You adapt to change, embrace bold ideas, and are intellectually curious. You like to ask questions, test assumptions, and challenge conventional thinking. You develop influential relationships based upon shared risk objectives and trust to deliver outstanding business impact. You're a teacher. You do the right thing and lead by example. You have a passion for coaching and investing in the betterment of your team. You lead through change with candor and optimism. You create energy and an environment that fosters trust, collaboration, and belonging, making it easy to attract, hire, and retain top talent. Basic Qualifications: Bachelor's degree or military experience At least 5 years of experience in Process, Project, Risk Management, or Cloud Risk Management At least 3 years direct experience with AI/ML model lifecycle management or operations or deployments Preferred Qualifications: Master's Degree in Computer Science or in an Engineering discipline At least 6 years of experience in Process, Project, Product, Risk Management, or Cloud Risk Management (or equivalent) At least 5 years of hands-on experience with AI/ML specific model lifecycle management including understanding of AI/ML architecture, model risk, data management and Responsible AI practices At least 4 years leading a team Effectively work in white space and bring structure to deliver on our well managed agenda Experience drafting and communicating reports or analytic assessments for executives Ability to communicate clearly and to interact effectively at all levels of the organization, and to influence as warranted and appropriate to drive consensus Experience with identifying and communicating key risks to AI implementations and architectures Experience with risk analysis and reports that describe risk implications to executives Ability to manage multiple high-visibility and high-impact projects while maintaining superior results Familiarity with AI/ML frameworks (NIST AI) Prior experience working in financial services or other highly regulated sectors Experience with security best practices for generative AI development and deployments At this time, Capital One will not sponsor a new 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. New York City (Hybrid On-Site): $233,100 - $266,000 for Director, Cyber Risk & Analysis 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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 . click apply for full job details
Locations: VA - McLean, United States of America, McLean, Virginia Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible) Sr Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems At least 6 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer Remote (Regardless of Location): $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: VA - McLean, United States of America, McLean, Virginia Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible) Sr Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems At least 6 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer Remote (Regardless of Location): $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
Locations: VA - McLean, United States of America, McLean, Virginia Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible) Sr Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems At least 6 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer Remote (Regardless of Location): $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).
04/19/2024
Full time
Locations: VA - McLean, United States of America, McLean, Virginia Sr Distinguished Engineer, Generative AI Systems - (Remote- Eligible) Sr Distinguished Engineer, Generative AI Systems Our mission at Capital One is to create trustworthy, reliable and human-in-the-loop 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. Because of our investments in public cloud infrastructure and machine learning platforms, we are now uniquely positioned to harness the power of AI. 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. We are looking for an experienced Senior Distinguished Engineer, AI Systems, to help us build the foundations of our enterprise AI Capabilities. You will work on a wide range of initiatives, whether that's designing robust, secure infrastructure, building large-scale distributed training clusters, deploying LLMs on GPU instances for real-time use cases, or supporting cutting-edge AI research and development, all in our public cloud infrastructure. You will work with a team of AI engineers and researchers to envision the target state of our capabilities while helping to design and implement key services. Examples of projects you will work on include: Design and build fault-tolerant infrastructure to support long-running large-scale training tasks reliably despite failure of individual nodes, using containers and check-pointing libraries. Design and build infrastructure for serving large ML models, in our public cloud. Deploy a thousand-node training cluster optimizing storage and networking stack, with tightly coupled training pipelines to take advantage of multiple parallelism strategies, in our public cloud. Design and implement benchmarks to measure the performance of software systems within AI capabilities and make recommendations on technology selection Develop applications that leverage LLMs and FMs. Design and implement capabilities to support MLOps for foundation models. Capital One is open to hiring a Remote Employee for this opportunity Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 9 years of experience designing and building distributed computing HPC and large-scale ML systems At least 6 years of experience developing AI and ML algorithms in Python or C/C++ At least 3 years of experience with the full ML development lifecycle using AI and ML frameworks and public cloud. Preferred Qualifications: Master's degree or PhD in Engineering, Computer Science, a related technical field, or equivalent practical experience with a focus on modern AI techniques. Experience designing large-scale distributed platforms and/or systems in cloud environments such as AWS, Azure, or GCP. Experience architecting cloud systems for security, availability, performance, scalability, and cost. Experience with delivering very large models through the MLOps life cycle from exploration to serving. Experience with building GPU clusters in the public cloud with tightly-coupled storage and networking. Experience with the complete stack for distributed training of large models including ML compilers, distributed training frameworks, and ML development frameworks such as Pytorch, Tensorflow, Lightning etc. Experience with one or multiple areas of AI technology stack including prompt engineering, guardrails, vector databases/knowledge bases, LLM hosting and fine-tuning. Authored research publications in top peer-reviewed conferences, or industry-recognized contributions in the space of neural networks, distributed training and SysML. 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. New York City (Hybrid On-Site): $321,500 - $366,900 for Sr Distinguished Machine Learning Engineer San Francisco, California (Hybrid On-Site): $340,500 - $388,700 for Sr Distinguished Machine Learning Engineer Remote (Regardless of Location): $272,400 - $310,900 for Sr Distinguished Machine Learning Engineer 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 committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law. 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).