130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/26/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/25/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/25/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/25/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/25/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
03/25/2024
Full time
130 5th Ave (22130), United States of America, New York, New York Director, Generative AI 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. At Capital One, 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. We are looking for an experienced Director, Generative AI to help us build the foundations of our Generative AI platform. You will lead a team of AI engineers and applied scientists, and work on a wide range of initiatives, whether that's building large-scale distributed training clusters, optimizing training pipelines to underlying hardware/software stack, or deploying LLMs on GPU instances for real-time applications and decisioning systems, all in our public cloud infrastructure. You will work closely with other infrastructure and research teams to design and implement key capabilities of our platform. Examples of projects you will work on: 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 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 run-time infrastructure for serving large ML models such as LLMs and FMs in our public cloud as well as secure third-party cloud providers. Build infrastructure for deploying search indexes and embeddings in vector databases that will work closely with the rest of our platform. Develop SDKs and APIs for our user community to build agents, information retrieval and anomaly/fraud detection systems on our Gen AI platform. Basic Qualifications: Bachelor's degree in Computer Science, Computer Engineering or a technical field At least 7 years of experience designing and building large-scale ML systems At least 6 years of experience developing AI/ML algorithms in Python or C/C++ At least 5 years of experience leading teams of engineers and applied scientists At least 3 years of experience with the full ML development lifecycle using open-source AI/ML frameworks and public cloud Preferred Qualifications: Master's degree or PhD in Computer Science, a related technical field, or or equivalent practical experience with experience in leading applied science and engineering teams. Background in machine learning with experience in large scale training and deployment of deep neural nets and/or transformer architectures. Authored research publications in top peer-reviewed conferences, or industry-recognized open-source contributions in the space of neural networks, distributed training and SysML. Experience with machine learning frameworks such as TensorFlow or Pytorch, Lightning, Mosaic ML on GPU clusters with a focus on distributed training, checkpointing and fault-tolerance. Ability to move fast in an environment with ambiguity at times, and with competing priorities and deadlines. Experience at tech and product-driven companies/startups preferred. Ability to iterate rapidly with researchers and engineers to improve a product experience while building the core components of a platform. Experience working with public cloud infrastructure such as AWS, Azure or GCP. Familiarity with deploying large neural network models in demanding production environments. 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): $274,800 - $313,600 for Director, Machine Learning Engineering Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer 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).
Primary Details Time Type: Full time Worker Type: Employee The Opportunity QBE is on the lookout for a Lead Machine Learning Engineer with deep expertise in developing and deploying advanced machine learning models and solutions. This role is central to driving QBE's innovative insurance solutions forward, including Pricing, Machine Learning, and by leveraging the latest AI technologies. The ideal candidate will have a strong foundation in machine learning engineering, software development, and team leadership. Additionally, the role demands a creative approach to problem-solving, effective mentorship, and the ability to foster strong collaborative relationships across the organization. Primary Responsibilities Develop and implement machine learning models to drive innovations in fraud detection, pricing strategies, and claim processing, ensuring QBE's competitive edge in tech-driven insurance solutions. Collaborate closely with business analysts and data scientists to transform complex business needs into technical specifications, thereby driving actionable insights and enhancing underwriting, pricing, and claims performance. Lead the integration of machine learning models into production, focusing on scalability, reliability, and adherence to engineering best practices. Ensure the scalability and efficiency of machine learning deployments through robust infrastructure management, including developing and maintaining deployment pipelines. Engage in active mentorship and technical leadership within the team, promoting a culture of innovation, continuous learning, and quality. Manage cross-functional projects, coordinating with internal teams and external partners to prioritize activities and deliver on strategic objectives. Maintain compliance with regulatory requirements, ensuring all model implementations and documentation meet industry standards. Required Education • Bachelor's Degree or equivalent combination of education and work experience Required Experience • 5 years relevant experience Preferred Competencies/Skills Excellent project management, collaboration, and communication skills, capable of leading complex projects and influencing stakeholders at all levels. Excellent all-around software development skill in Python. Experience working in cloud environments such as Azure, AWS, or GCP and knowledge of their AI and ML services. Experience in running a large program or several projects simultaneously. Proficiency in SQL for analysis and data extraction. Advanced knowledge in machine learning engineering practices, including MLOps tools (MLflow, Kubeflow, TFX) to streamline the machine learning lifecycle. Familiarity with containerization and orchestration technologies (Docker, Kubernetes) for scalable ML deployments. Experience with TensorFlow, PyTorch, transformers, LangChain, numpy, pandas, polars, and related. Excellent communication and collaboration skills. Preferred Education Specifics Degree qualified (or equivalent) in Computer Science, Engineering, Machine Learning, Mathematics, Statistics, or related discipline 3+ years of experience with design and architecture, data structures, and testing/launching software products. 2+ years in ML engineering with production-level deployments. Preferred Licenses/Certifications • Certified Specialist in Predictive Analytics (CAS) or other data science related certifications Preferred Knowledge Strong understanding of data and model quality monitoring systems, and developing data validation frameworks. Expertise in advanced model optimization techniques, including fine-tuning and the development and deployment of Retrieval-Augmented Generation (RAG) models for enhanced AI performance. Proficient in Git and trunk-based branching strategies. Guide the team in adopting CI/CD practices, code review processes, and automated testing frameworks for ML systems. Strong understanding of software design principles. Skilled in implementing data and model quality monitoring systems and developing data validation frameworks. Proven proficiency in developing and executing Bash scripts for automation and system management tasks. Understand policyholder characteristics and insurance product attributes as needed to improve model performance. Creativity and curiosity for solving complex problems. About QBE We can never really predict what's around the corner, but at QBE we're asking the right questions to enable a more resilient future by helping those around us build strength and embrace change to their advantage. We're an international insurer that's building momentum towards realizing our vision of becoming the most consistent and innovative risk partner. And our people will be at the center of our success. We're proud to work together, and encourage each other to enable resilience for our customers, our environment, our economies and our communities. With more than 12,000 people working across 27 countries, we're big enough to make a real impact, but small enough to provide a friendly workplace, where people are down-to-earth, passionate, and kind. We believe this is our moment: What if it was yours too? Your career at QBE - let's make it happen! US Only - Travel Frequency • Infrequent (approximately 1-4 trips annually) US Only - Physical Demands • General office jobs: Work is generally performed in an office environment in which there is not substantial exposure to adverse environmental conditions. Must have the ability to remain in a stationary position for extended periods of time. Must be able to operate basic office equipment including telephone, headset and computer. Incumbent must be able to lift basic office equipment up to 20 lbs. US Only - Disclaimer • To successfully perform this job, the individual must be able to perform each essential job responsibility satisfactorily. Reasonable accommodations may be made to enable an individual with disabilities to perform the essential job responsibilities. Job Type • Individual Contributor Global Disclaimer • The duties listed in this job description do not limit the assignment of work. They are not to be construed as a complete list of the duties normally to be performed in the position or those occasionally assigned outside an employee's normal duties. Our Group Code of Ethics and Conduct addresses the responsibilities we all have at QBE to our company, to each other and to our customers, suppliers, communities and governments. It provides clear guidance to help us to make good judgement calls. Compensation Base pay offered will vary depending on, but not limited to education, experience, skills, geographic location and business needs. Annual Salary Range: $121,000 - $182,000 AL, AR, AZ, CO (Remote), DE, FL, GA, IA, ID, IL (Remote), IN, KS, KY, LA, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NV, OH, OK, OR, PA, SC, SD, TN, TX (Remote, Plano), UT, VA, VT, WI, WV and WY Annual Salary Range: $133,000 - $200,000 CA (Remote, Fresno, Irvine and Woodland), Greenwood Village CO, CT, Chicago IL, MA, MD, NY (Remote), RI, Houston TX and WA Annual Salary Range: $152,000 - $228,000 San Francisco CA, NJ and New York City NY Benefit Highlights You are more than your work - and QBE is more than a workplace, which is why QBE provides you with the benefits, support and flexibility to help you concentrate on living your best life personally and professionally. Employees scheduled over 30 hours a week will have access to comprehensive medical, dental, vision and wellbeing benefits that enable you to take care of your health. We also offer a competitive 401(k) contribution and a paid-time off program. In addition, our paid-family and care-giver leaves are available to support our employees and their families. Regular full-time and part-time employees will also be eligible for QBE's annual discretionary bonus plan based on business and individual performance. At QBE, we understand that exceptional employee benefits go beyond mere coverage and compensation. We recognize the importance of flexibility in the work environment to promote a healthy balance, and we are committed to facilitating personal and professional integration for our employees. That's why we offer the opportunity for hybrid work arrangements. If this role necessitates a hybrid working model, candidates must be open to attending the office 8-12 days per month. This approach ensures a collaborative and supportive work environment where team members can come together to innovate and drive success. How to Apply: To submit your application, click "Apply" and follow the step by step process. Equal Employment Opportunity: QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates.
03/23/2024
Full time
Primary Details Time Type: Full time Worker Type: Employee The Opportunity QBE is on the lookout for a Lead Machine Learning Engineer with deep expertise in developing and deploying advanced machine learning models and solutions. This role is central to driving QBE's innovative insurance solutions forward, including Pricing, Machine Learning, and by leveraging the latest AI technologies. The ideal candidate will have a strong foundation in machine learning engineering, software development, and team leadership. Additionally, the role demands a creative approach to problem-solving, effective mentorship, and the ability to foster strong collaborative relationships across the organization. Primary Responsibilities Develop and implement machine learning models to drive innovations in fraud detection, pricing strategies, and claim processing, ensuring QBE's competitive edge in tech-driven insurance solutions. Collaborate closely with business analysts and data scientists to transform complex business needs into technical specifications, thereby driving actionable insights and enhancing underwriting, pricing, and claims performance. Lead the integration of machine learning models into production, focusing on scalability, reliability, and adherence to engineering best practices. Ensure the scalability and efficiency of machine learning deployments through robust infrastructure management, including developing and maintaining deployment pipelines. Engage in active mentorship and technical leadership within the team, promoting a culture of innovation, continuous learning, and quality. Manage cross-functional projects, coordinating with internal teams and external partners to prioritize activities and deliver on strategic objectives. Maintain compliance with regulatory requirements, ensuring all model implementations and documentation meet industry standards. Required Education • Bachelor's Degree or equivalent combination of education and work experience Required Experience • 5 years relevant experience Preferred Competencies/Skills Excellent project management, collaboration, and communication skills, capable of leading complex projects and influencing stakeholders at all levels. Excellent all-around software development skill in Python. Experience working in cloud environments such as Azure, AWS, or GCP and knowledge of their AI and ML services. Experience in running a large program or several projects simultaneously. Proficiency in SQL for analysis and data extraction. Advanced knowledge in machine learning engineering practices, including MLOps tools (MLflow, Kubeflow, TFX) to streamline the machine learning lifecycle. Familiarity with containerization and orchestration technologies (Docker, Kubernetes) for scalable ML deployments. Experience with TensorFlow, PyTorch, transformers, LangChain, numpy, pandas, polars, and related. Excellent communication and collaboration skills. Preferred Education Specifics Degree qualified (or equivalent) in Computer Science, Engineering, Machine Learning, Mathematics, Statistics, or related discipline 3+ years of experience with design and architecture, data structures, and testing/launching software products. 2+ years in ML engineering with production-level deployments. Preferred Licenses/Certifications • Certified Specialist in Predictive Analytics (CAS) or other data science related certifications Preferred Knowledge Strong understanding of data and model quality monitoring systems, and developing data validation frameworks. Expertise in advanced model optimization techniques, including fine-tuning and the development and deployment of Retrieval-Augmented Generation (RAG) models for enhanced AI performance. Proficient in Git and trunk-based branching strategies. Guide the team in adopting CI/CD practices, code review processes, and automated testing frameworks for ML systems. Strong understanding of software design principles. Skilled in implementing data and model quality monitoring systems and developing data validation frameworks. Proven proficiency in developing and executing Bash scripts for automation and system management tasks. Understand policyholder characteristics and insurance product attributes as needed to improve model performance. Creativity and curiosity for solving complex problems. About QBE We can never really predict what's around the corner, but at QBE we're asking the right questions to enable a more resilient future by helping those around us build strength and embrace change to their advantage. We're an international insurer that's building momentum towards realizing our vision of becoming the most consistent and innovative risk partner. And our people will be at the center of our success. We're proud to work together, and encourage each other to enable resilience for our customers, our environment, our economies and our communities. With more than 12,000 people working across 27 countries, we're big enough to make a real impact, but small enough to provide a friendly workplace, where people are down-to-earth, passionate, and kind. We believe this is our moment: What if it was yours too? Your career at QBE - let's make it happen! US Only - Travel Frequency • Infrequent (approximately 1-4 trips annually) US Only - Physical Demands • General office jobs: Work is generally performed in an office environment in which there is not substantial exposure to adverse environmental conditions. Must have the ability to remain in a stationary position for extended periods of time. Must be able to operate basic office equipment including telephone, headset and computer. Incumbent must be able to lift basic office equipment up to 20 lbs. US Only - Disclaimer • To successfully perform this job, the individual must be able to perform each essential job responsibility satisfactorily. Reasonable accommodations may be made to enable an individual with disabilities to perform the essential job responsibilities. Job Type • Individual Contributor Global Disclaimer • The duties listed in this job description do not limit the assignment of work. They are not to be construed as a complete list of the duties normally to be performed in the position or those occasionally assigned outside an employee's normal duties. Our Group Code of Ethics and Conduct addresses the responsibilities we all have at QBE to our company, to each other and to our customers, suppliers, communities and governments. It provides clear guidance to help us to make good judgement calls. Compensation Base pay offered will vary depending on, but not limited to education, experience, skills, geographic location and business needs. Annual Salary Range: $121,000 - $182,000 AL, AR, AZ, CO (Remote), DE, FL, GA, IA, ID, IL (Remote), IN, KS, KY, LA, ME, MI, MN, MO, MS, MT, NC, ND, NE, NH, NV, OH, OK, OR, PA, SC, SD, TN, TX (Remote, Plano), UT, VA, VT, WI, WV and WY Annual Salary Range: $133,000 - $200,000 CA (Remote, Fresno, Irvine and Woodland), Greenwood Village CO, CT, Chicago IL, MA, MD, NY (Remote), RI, Houston TX and WA Annual Salary Range: $152,000 - $228,000 San Francisco CA, NJ and New York City NY Benefit Highlights You are more than your work - and QBE is more than a workplace, which is why QBE provides you with the benefits, support and flexibility to help you concentrate on living your best life personally and professionally. Employees scheduled over 30 hours a week will have access to comprehensive medical, dental, vision and wellbeing benefits that enable you to take care of your health. We also offer a competitive 401(k) contribution and a paid-time off program. In addition, our paid-family and care-giver leaves are available to support our employees and their families. Regular full-time and part-time employees will also be eligible for QBE's annual discretionary bonus plan based on business and individual performance. At QBE, we understand that exceptional employee benefits go beyond mere coverage and compensation. We recognize the importance of flexibility in the work environment to promote a healthy balance, and we are committed to facilitating personal and professional integration for our employees. That's why we offer the opportunity for hybrid work arrangements. If this role necessitates a hybrid working model, candidates must be open to attending the office 8-12 days per month. This approach ensures a collaborative and supportive work environment where team members can come together to innovate and drive success. How to Apply: To submit your application, click "Apply" and follow the step by step process. Equal Employment Opportunity: QBE is an equal opportunity employer and is required to comply with equal employment opportunity legislation in each jurisdiction it operates.
Help us change lives At Exact Sciences, we're helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you're working to help others. Position Overview The Senior Clinical Laboratory Scientist will be responsible for performing high complexity laboratory testing on patient specimens, interpreting and reporting patient results, performing quality control and quality assurance procedures, assisting Lead Clinical Laboratory Scientists with advanced laboratory duties, and complying with all applicable local, state, and federal laboratory requirements. The Senior Clinical Laboratory Scientist will continually display excellent initiative in all aspects of their work, contribute to projects and discussions in addition to daily laboratory testing and consistently performing to high standards. Leadership is demonstrated in technical troubleshooting of laboratory instrumentation and processes as well as laboratory quality improvements, health and safety, and training of laboratory staff. Locations: 650 Forward Drive & 145 E. Badger Road Essential Duties include but are not limited to : Perform laboratory tests, procedures, and analyses according to the laboratory's standard operating procedures. Perform, review, and document laboratory quality control procedures. Operate, maintain, and troubleshoot laboratory equipment. Prepare reagents required for laboratory testing. Identify and troubleshoot basic problems that adversely affect test performance. Review, interpret, and approve patient results as needed. Maintain sufficient inventory of laboratory supplies for daily operations. Participate in testing and validation of new laboratory equipment and procedures, as needed. Maintain stringent standards for quality, identifying any issues which might adversely impact the quality of test results and/or employee safety, and communicating these to the appropriate management representatives as necessary for resolution. Manage daily test processing needs along with project needs in a high quality, efficient and effective manner. Communicate effectively with ability to maintain open communication with internal employees, managers, and customers, as needed. Participate in quality assurance and inspection preparation activities. Integrate and apply feedback in a professional manner. Participate in continuing education and staff meetings. Responsible for own professional development. Meet productivity and TAT expectations. Work as part of a team. Multi-task and be flexible with tasks and schedules. Excellent attention to detail. Effective written and verbal communication skills. Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. Demonstrate adaptability by embracing changes in the laboratory with a positive attitude. Support and comply with the company's Quality Management System policies and procedures. Maintain regular and reliable attendance. Act with an inclusive mindset. Work a designated schedule. Ability to work overtime, as needed. Ability to lift up to 40 pounds for approximately 25% of a typical working day. Ability to work seated for approximately 50% of a typical working day. Ability to work standing for approximately 50% of a typical working day. Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 75% of a typical working day. Ability to perform technical work up to 80% of a typical working day and administrative work up to 20% of a typical working day. Ability to grasp with both hands; pinch with thumb and forefinger; turn with hand/arm; reach above shoulder height. Ability to use various types of laboratory equipment and perform repetitive motions. Ability to comply with any applicable personal protective equipment requirements. Comply with safety and hazard regulations as outlined in the clinical laboratory safety manual. May be exposed to hazardous materials, tissue specimens, blood or blood products and instruments with moving parts, lasers, heating and freezing elements, and high-speed centrifugation. Observe principles of data security and patient confidentiality. Maintain ethical standards in the performance of testing and in interactions with patients, co-workers, and other health care professionals. Travel between Madison Laboratory locations may be required. Perform job duties as expected of a Clinical Laboratory Scientist. Perform training and competency tasks with laboratory personnel on current and new procedures. Provide leadership in daily activities as a shift senior scientist. Assist the laboratory supervisors; including but not limited to, writing, and reviewing procedures, documents, and forms, and assisting in developing the troubleshooting and decision-making skills of the Clinical Laboratory Scientists. Oversees the activities and provides guidance and constructive feedback to clinical laboratory scientists I and II. Ability to recognize deviations from the accepted practice and perform deep root cause analysis. Professional demeanor and behavior in all work-related interactions. Ability to respond to stakeholder requests in a professional and timely manner. Minimum Qualifications Associate degree in a laboratory science (chemical or biological science) or medical laboratory technology from an accredited institution. Or equivalent laboratory training and experience as defined: 60 semester hours or equivalent from an accredited institution that, at a minimum, includes either 24 semester hours of medical laboratory technology courses, OR 24 semester hours of science courses that include six semester hours of chemistry, six semester hours of biology, and 12 semester hours of chemistry, biology or medical laboratory technology in any combination. 3+ years of high complexity clinical testing experience in a clinical laboratory setting. Demonstrated strong professionalism and leadership skills. Demonstrated intermediate level project management skills. Demonstrated strong technical skills and professional working knowledge of job industry. Demonstrated ability to perform the Essential Duties of the position with or without accommodation. Authorization to work in the United States without sponsorship. Preferred Qualifications Bachelor's degree in a chemical, physical, biological or clinical laboratory science or medical technology from an accredited institution. For degree not in those listed above: 90 semester hours which must include 16 semester hours in chemistry (6 of which must be in inorganic chemistry); 16 semester hours in biology courses and 3 semester hours of math. Certification from one of the nationally recognized certification agencies such as ASCP or state licensure that has been determined to be equivalent. Experience with laboratory automation. Experience working with laboratory information systems. LI-ER1Salary Range: $50,000.00 - $81,000.00 The annual base salary shown is for this position located in US - WI - Madison on a full-time basis. In addition, this position is bonus eligible, and is eligible to receive company stock upon hire as well as annually.Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits . Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, email . We'll work with you to meet your accessibility needs. Not ready to apply? Join our talent community and stay up to date on what's new at Exact Sciences. We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, creed, disability, gender identity, national origin, protected veteran status, race, religion, sex, sexual orientation, and any other status protected by applicable local, state, or federal law. Any applicant or employee may request to view applicable portions of the company's affirmative action program. To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub . The documents summarize important details of the law and provide key points that you have a right to know.
03/17/2024
Full time
Help us change lives At Exact Sciences, we're helping change how the world prevents, detects and guides treatment for cancer. We give patients and clinicians the clarity needed to make confident decisions when they matter most. Join our team to find a purpose-driven career, an inclusive culture, and robust benefits to support your life while you're working to help others. Position Overview The Senior Clinical Laboratory Scientist will be responsible for performing high complexity laboratory testing on patient specimens, interpreting and reporting patient results, performing quality control and quality assurance procedures, assisting Lead Clinical Laboratory Scientists with advanced laboratory duties, and complying with all applicable local, state, and federal laboratory requirements. The Senior Clinical Laboratory Scientist will continually display excellent initiative in all aspects of their work, contribute to projects and discussions in addition to daily laboratory testing and consistently performing to high standards. Leadership is demonstrated in technical troubleshooting of laboratory instrumentation and processes as well as laboratory quality improvements, health and safety, and training of laboratory staff. Locations: 650 Forward Drive & 145 E. Badger Road Essential Duties include but are not limited to : Perform laboratory tests, procedures, and analyses according to the laboratory's standard operating procedures. Perform, review, and document laboratory quality control procedures. Operate, maintain, and troubleshoot laboratory equipment. Prepare reagents required for laboratory testing. Identify and troubleshoot basic problems that adversely affect test performance. Review, interpret, and approve patient results as needed. Maintain sufficient inventory of laboratory supplies for daily operations. Participate in testing and validation of new laboratory equipment and procedures, as needed. Maintain stringent standards for quality, identifying any issues which might adversely impact the quality of test results and/or employee safety, and communicating these to the appropriate management representatives as necessary for resolution. Manage daily test processing needs along with project needs in a high quality, efficient and effective manner. Communicate effectively with ability to maintain open communication with internal employees, managers, and customers, as needed. Participate in quality assurance and inspection preparation activities. Integrate and apply feedback in a professional manner. Participate in continuing education and staff meetings. Responsible for own professional development. Meet productivity and TAT expectations. Work as part of a team. Multi-task and be flexible with tasks and schedules. Excellent attention to detail. Effective written and verbal communication skills. Uphold company mission and values through accountability, innovation, integrity, quality, and teamwork. Demonstrate adaptability by embracing changes in the laboratory with a positive attitude. Support and comply with the company's Quality Management System policies and procedures. Maintain regular and reliable attendance. Act with an inclusive mindset. Work a designated schedule. Ability to work overtime, as needed. Ability to lift up to 40 pounds for approximately 25% of a typical working day. Ability to work seated for approximately 50% of a typical working day. Ability to work standing for approximately 50% of a typical working day. Ability to work on a mobile device, tablet, or in front of a computer screen and/or perform typing for approximately 75% of a typical working day. Ability to perform technical work up to 80% of a typical working day and administrative work up to 20% of a typical working day. Ability to grasp with both hands; pinch with thumb and forefinger; turn with hand/arm; reach above shoulder height. Ability to use various types of laboratory equipment and perform repetitive motions. Ability to comply with any applicable personal protective equipment requirements. Comply with safety and hazard regulations as outlined in the clinical laboratory safety manual. May be exposed to hazardous materials, tissue specimens, blood or blood products and instruments with moving parts, lasers, heating and freezing elements, and high-speed centrifugation. Observe principles of data security and patient confidentiality. Maintain ethical standards in the performance of testing and in interactions with patients, co-workers, and other health care professionals. Travel between Madison Laboratory locations may be required. Perform job duties as expected of a Clinical Laboratory Scientist. Perform training and competency tasks with laboratory personnel on current and new procedures. Provide leadership in daily activities as a shift senior scientist. Assist the laboratory supervisors; including but not limited to, writing, and reviewing procedures, documents, and forms, and assisting in developing the troubleshooting and decision-making skills of the Clinical Laboratory Scientists. Oversees the activities and provides guidance and constructive feedback to clinical laboratory scientists I and II. Ability to recognize deviations from the accepted practice and perform deep root cause analysis. Professional demeanor and behavior in all work-related interactions. Ability to respond to stakeholder requests in a professional and timely manner. Minimum Qualifications Associate degree in a laboratory science (chemical or biological science) or medical laboratory technology from an accredited institution. Or equivalent laboratory training and experience as defined: 60 semester hours or equivalent from an accredited institution that, at a minimum, includes either 24 semester hours of medical laboratory technology courses, OR 24 semester hours of science courses that include six semester hours of chemistry, six semester hours of biology, and 12 semester hours of chemistry, biology or medical laboratory technology in any combination. 3+ years of high complexity clinical testing experience in a clinical laboratory setting. Demonstrated strong professionalism and leadership skills. Demonstrated intermediate level project management skills. Demonstrated strong technical skills and professional working knowledge of job industry. Demonstrated ability to perform the Essential Duties of the position with or without accommodation. Authorization to work in the United States without sponsorship. Preferred Qualifications Bachelor's degree in a chemical, physical, biological or clinical laboratory science or medical technology from an accredited institution. For degree not in those listed above: 90 semester hours which must include 16 semester hours in chemistry (6 of which must be in inorganic chemistry); 16 semester hours in biology courses and 3 semester hours of math. Certification from one of the nationally recognized certification agencies such as ASCP or state licensure that has been determined to be equivalent. Experience with laboratory automation. Experience working with laboratory information systems. LI-ER1Salary Range: $50,000.00 - $81,000.00 The annual base salary shown is for this position located in US - WI - Madison on a full-time basis. In addition, this position is bonus eligible, and is eligible to receive company stock upon hire as well as annually.Exact Sciences is proud to offer an employee experience that includes paid time off (including days for vacation, holidays, volunteering, and personal time), paid leave for parents and caregivers, a retirement savings plan, wellness support, and health benefits including medical, prescription drug, dental, and vision coverage. Learn more about our benefits . Our success relies on the experiences and perspectives of a diverse team, and Exact Sciences fosters a culture where all employees can develop personally and professionally with a sense of respect and belonging. If you require an accommodation, email . We'll work with you to meet your accessibility needs. Not ready to apply? Join our talent community and stay up to date on what's new at Exact Sciences. We are an equal employment opportunity employer. All qualified applicants will receive consideration for employment without regard to age, color, creed, disability, gender identity, national origin, protected veteran status, race, religion, sex, sexual orientation, and any other status protected by applicable local, state, or federal law. Any applicant or employee may request to view applicable portions of the company's affirmative action program. To view the Right to Work, E-Verify Employer, and Pay Transparency notices and Federal, Federal Contractor, and State employment law posters, visit our compliance hub . The documents summarize important details of the law and provide key points that you have a right to know.
About SwanBio Therapeutics SwanBio is a privately held, newly established biotechnology company focused on the discovery and development of innovative gene therapy products for the treatment of central nervous system (CNS) disorders and diseases. SwanBio has a deeply experienced leadership team and is building an open, innovative culture that trusts its people, processes and science to deliver scientific, clinical and business success. SwanBio's lead investor is Syncona, a premiere investment partner focused on building companies delivering transformational healthcare treatments. Syncona has a deep pool of capital and they are established leaders in the development of genetic medicine. In particular, they present a legacy of success in long term investment strategies for companies in the Gene and Cell Therapy space. Our goal is to become a world-leader in treating neurodegenerative diseases. With locations in Philadelphia and Boston, the SwanBio Team is building a strong pipeline of gene therapy development programs with a directed focus on critical unmet medical needs for CNS diseases. SwanBio offers all team members both competitive compensation and benefits. The Opportunity We are seeking a highly motivated molecular biologist to join our Vector Engineering group and play a critical role in designing and evaluating novel vectors for our gene therapy pipeline. The position offers an exciting opportunity to engage in the discovery and molecular engineering of Biotherapeutics for unmet medical needs. Key Responsibilities In this role you will: Perform molecular biology tasks such as plasmid preps, cloning, construct design, RNA extraction, site-directed mutagenesis, and expression vector engineering Perform mammalian cell culture and biochemical assays such as qPCR, ddPCR, western blot, ELISA Assist in the design and execution of non-routine experiments in an efficient and independent manner Demonstrate the ability interpret outcome of experiments and to propose appropriate follow-up Report and treat data with a high level of integrity and ethics Troubleshoot problems as needed Participate in cross-function initiatives as needed Independently present/defend scientific findings in project team or Department meetings Perform literature searches and extract relevant information from published protocols Communicate own work effectively orally and in writing Contribute to writing protocols, procedures, and technical reports; provide input for scientific reports Comply with applicable regulations and perform all work in a safe manner Maintain proper records in accordance with SOPs and policies Basic Requirements: BS degree in molecular biology, biochemistry, neuroscience or a related discipline plus at least 5 years' relevant experience OR a Masters' Degree plus at least 3 years' relevant experience (preferably in an industry setting) Hands-on experience in Molecular Biology techniques such as construct design, cloning, plasmid prep, DNA sequence analysis Previous vector engineering experience Experience in cell line maintenance and bioassays such as qPCR, western blot, ELISA Ability to concisely and accurately report technical data and information Ability to troubleshoot and correct problems Appropriate level of understanding of applicable regulations Experience with oversight of CROs preferred Skills: Excellent written and verbal communication skills Outstanding problem-solving skills Ability to be highly productive in a fluid, fast-paced and team-oriented work environment Strong collaboration and team-working skills Strong interpersonal and organizational skills Proven ability to work independently and effectively plan and organize work activities and prioritize task completion to meet deadlines Possess a mindset of no job too large or too small. About the Benefits: The successful candidate will enjoy a competitive base salary and the opportunity to participate in incentive compensation programs including bonus. Additionally, SwanBio Therapeutics offers all team members a comprehensive benefits program including medical, dental, vision care, 401(k), paid vacation and holiday time. SwanBio Therapeutics is an equal opportunity employer
01/29/2021
Full time
About SwanBio Therapeutics SwanBio is a privately held, newly established biotechnology company focused on the discovery and development of innovative gene therapy products for the treatment of central nervous system (CNS) disorders and diseases. SwanBio has a deeply experienced leadership team and is building an open, innovative culture that trusts its people, processes and science to deliver scientific, clinical and business success. SwanBio's lead investor is Syncona, a premiere investment partner focused on building companies delivering transformational healthcare treatments. Syncona has a deep pool of capital and they are established leaders in the development of genetic medicine. In particular, they present a legacy of success in long term investment strategies for companies in the Gene and Cell Therapy space. Our goal is to become a world-leader in treating neurodegenerative diseases. With locations in Philadelphia and Boston, the SwanBio Team is building a strong pipeline of gene therapy development programs with a directed focus on critical unmet medical needs for CNS diseases. SwanBio offers all team members both competitive compensation and benefits. The Opportunity We are seeking a highly motivated molecular biologist to join our Vector Engineering group and play a critical role in designing and evaluating novel vectors for our gene therapy pipeline. The position offers an exciting opportunity to engage in the discovery and molecular engineering of Biotherapeutics for unmet medical needs. Key Responsibilities In this role you will: Perform molecular biology tasks such as plasmid preps, cloning, construct design, RNA extraction, site-directed mutagenesis, and expression vector engineering Perform mammalian cell culture and biochemical assays such as qPCR, ddPCR, western blot, ELISA Assist in the design and execution of non-routine experiments in an efficient and independent manner Demonstrate the ability interpret outcome of experiments and to propose appropriate follow-up Report and treat data with a high level of integrity and ethics Troubleshoot problems as needed Participate in cross-function initiatives as needed Independently present/defend scientific findings in project team or Department meetings Perform literature searches and extract relevant information from published protocols Communicate own work effectively orally and in writing Contribute to writing protocols, procedures, and technical reports; provide input for scientific reports Comply with applicable regulations and perform all work in a safe manner Maintain proper records in accordance with SOPs and policies Basic Requirements: BS degree in molecular biology, biochemistry, neuroscience or a related discipline plus at least 5 years' relevant experience OR a Masters' Degree plus at least 3 years' relevant experience (preferably in an industry setting) Hands-on experience in Molecular Biology techniques such as construct design, cloning, plasmid prep, DNA sequence analysis Previous vector engineering experience Experience in cell line maintenance and bioassays such as qPCR, western blot, ELISA Ability to concisely and accurately report technical data and information Ability to troubleshoot and correct problems Appropriate level of understanding of applicable regulations Experience with oversight of CROs preferred Skills: Excellent written and verbal communication skills Outstanding problem-solving skills Ability to be highly productive in a fluid, fast-paced and team-oriented work environment Strong collaboration and team-working skills Strong interpersonal and organizational skills Proven ability to work independently and effectively plan and organize work activities and prioritize task completion to meet deadlines Possess a mindset of no job too large or too small. About the Benefits: The successful candidate will enjoy a competitive base salary and the opportunity to participate in incentive compensation programs including bonus. Additionally, SwanBio Therapeutics offers all team members a comprehensive benefits program including medical, dental, vision care, 401(k), paid vacation and holiday time. SwanBio Therapeutics is an equal opportunity employer
Description Job Description: Leidos is a Fortune 500™ company aimed at embracing and solving some of the world's most pressing challenges. Through science and technology, Leidos makes the world safer, healthier and more efficient. Our Civil Group offers an array of exciting career opportunities for the best IT, energy, logistics and engineering professionals. Leidos is seeking a Communications Editor that will be responsible for writing, editing and managing the online Antarctic Sun newspaper ( antarcticsun.usap.gov ), creating multi-media products, and serving as photographer and manager of the USAP Photo Library archive ( photolibrary.usap.gov ). The Communications Editor will create a budget of story ideas and timelines, conduct interviews, write articles, take photographs, edit, obtain approvals, and publish news and feature content about the U.S. Antarctic Program (USAP) research and operations. All stories are reviewed by subject matter experts, ASC Communications Manager, and the appropriate people at the National Science Foundation for accuracy and content. Other duties include public-facing activities such as: Interacting with the public to promote awareness of the USAP through public presentations and media events Responding to media and public queries Developing materials for and facilitating education outreach Additional internal duties include: Interacting with the National Science Foundation Providing editorial and writing assistance to the Antarctic Support Contract (ASC) Facilitating internal communications through bulletin boards, creation of flyers, composing programmatic emails, and managing All Hands meetings Writing updates, articles and blogs for Leidos Other duties as assigned The Communications Editor will report directly to the ASC Communications Manager. In addition, as a member of the Communications Department, the position will help develop, coordinate and execute field plans for media, film and other groups should they deploy. Duties include working with the teams to identify their requirements for achieving their goals, prior to their deployment, coordinating within the USAP to help facilitate the support needed for them, and working with them directly in Antarctica to facilitate their project. Required Qualifications: Bachelor's Degree in Multimedia Journalism or related field, additional years of experience will be considered in lieu of degree. A minimum of 3 years of experience as a science editor/writer or journalist, with significant experience as a photographer, videographer or photojournalist. Ease of use and understanding of social media platforms such as Facebook and Twitter. Excellent spelling and grammar, as well as experience with AP style are required. Knowledge of and competency in understanding copyright law regarding original works of writing and photography. Proficiency with Microsoft Office and Adobe Create Suite. At least 2 years' experience using Adobe software, with excellent Photoshop or LightRoom skills, and InDesign graphic layout and design experience. At least 2 years' experience creating and editing multi-media publications such as podcasts and/or video stories. Experience and ease with public speaking and be willing to represent both ASC and the USAP in public forums. Must work independently, manage time and meet deadlines. Have good organizational skills to track, coordinate and adapt to frequently-changing logistics plans and schedules. Ability and motivation to quickly learn the workings of a large, complex program and become a de facto "expert" on Antarctica and the U.S. Antarctic Program. Must interact in a professional manner with National Science Foundation staff, scientists and other USAP agencies and stakeholders. Additional Application Requirements: In addition to resume please submit the following: 3 examples of professionally published articles from your portfolio illustrating how a complex topic was distilled into an accurate and compelling article for the general public; 2 examples of an original graphic layout such as a brochure or flyer. PHYSICAL AND / OR OTHER SPECIFIC REQUIREMENTS: Deployment to Antarctica is required for this position. The individual in the position must successfully complete the physical and dental examinations as required by the NSF for deploying to Antarctica. Failure to meet these requirements may result in withdrawal of employment offer or other employment action. Applicant must be willing to deploy to Antarctica for 1-6 months annually (typically 3-4 months) based on business/program needs. Preferred Qualifications: A general understanding of the Internet, website layout, general multimedia production, and web content management applications is needed. This position does not create websites, but does need to place content into a content management application and work closely with the multi-media team. Driven by our talented workforce, the Integrated Missions Operation builds trust through an array of energy-related IT, environmental science and engineering solutions to meet our customers' needs. Key Programs and/or Capabilities: Antarctic Support Contract (ASC) Large Infrastructure Mission Support Digital Modernization Command & Control Mission Applications Science Energy and Environment Engineering Services Leidos is growing! Connect with us on LinkedIn and Facebook . We value and support the well-being and mobility of our employees with competitive benefit packages, complementary e-learning training, work-life flexibility, an exciting External Referral Program , and a diverse, inclusive and ethical work place. In fact, in 2020, Leidos was ranked as one of the "World's Most Ethical Companies" by the Ethisphere Institute for the third consecutive year. External Referral Bonus: Ineligible Potential for Telework: Yes, 25% Clearance Level Required: None Travel: Yes, 50% of the time Scheduled Weekly Hours: 40 Shift: Day Requisition Category: Professional Job Family: Writing and Editing Pay Range: Pay Range $48,750.00 - $75,000.00 - $101,250.00 Leidos is a Fortune 500 ® information technology, engineering, and science solutions and services leader working to solve the world's toughest challenges in the defense, intelligence, homeland security, civil, and health markets. The company's 38,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Va., Leidos reported annual revenues of approximately $11.09 billion for the fiscal year ended January 3, 2020. For more information, visit . Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here . Leidos will never ask you to provide payment-related information at any part of the employment application process. And Leidos will communicate with you only through emails that are sent from a Leidos.com email address. If you receive an email purporting to be from Leidos that asks for payment-related information or any other personal information, please report the email to . All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.
01/25/2021
Full time
Description Job Description: Leidos is a Fortune 500™ company aimed at embracing and solving some of the world's most pressing challenges. Through science and technology, Leidos makes the world safer, healthier and more efficient. Our Civil Group offers an array of exciting career opportunities for the best IT, energy, logistics and engineering professionals. Leidos is seeking a Communications Editor that will be responsible for writing, editing and managing the online Antarctic Sun newspaper ( antarcticsun.usap.gov ), creating multi-media products, and serving as photographer and manager of the USAP Photo Library archive ( photolibrary.usap.gov ). The Communications Editor will create a budget of story ideas and timelines, conduct interviews, write articles, take photographs, edit, obtain approvals, and publish news and feature content about the U.S. Antarctic Program (USAP) research and operations. All stories are reviewed by subject matter experts, ASC Communications Manager, and the appropriate people at the National Science Foundation for accuracy and content. Other duties include public-facing activities such as: Interacting with the public to promote awareness of the USAP through public presentations and media events Responding to media and public queries Developing materials for and facilitating education outreach Additional internal duties include: Interacting with the National Science Foundation Providing editorial and writing assistance to the Antarctic Support Contract (ASC) Facilitating internal communications through bulletin boards, creation of flyers, composing programmatic emails, and managing All Hands meetings Writing updates, articles and blogs for Leidos Other duties as assigned The Communications Editor will report directly to the ASC Communications Manager. In addition, as a member of the Communications Department, the position will help develop, coordinate and execute field plans for media, film and other groups should they deploy. Duties include working with the teams to identify their requirements for achieving their goals, prior to their deployment, coordinating within the USAP to help facilitate the support needed for them, and working with them directly in Antarctica to facilitate their project. Required Qualifications: Bachelor's Degree in Multimedia Journalism or related field, additional years of experience will be considered in lieu of degree. A minimum of 3 years of experience as a science editor/writer or journalist, with significant experience as a photographer, videographer or photojournalist. Ease of use and understanding of social media platforms such as Facebook and Twitter. Excellent spelling and grammar, as well as experience with AP style are required. Knowledge of and competency in understanding copyright law regarding original works of writing and photography. Proficiency with Microsoft Office and Adobe Create Suite. At least 2 years' experience using Adobe software, with excellent Photoshop or LightRoom skills, and InDesign graphic layout and design experience. At least 2 years' experience creating and editing multi-media publications such as podcasts and/or video stories. Experience and ease with public speaking and be willing to represent both ASC and the USAP in public forums. Must work independently, manage time and meet deadlines. Have good organizational skills to track, coordinate and adapt to frequently-changing logistics plans and schedules. Ability and motivation to quickly learn the workings of a large, complex program and become a de facto "expert" on Antarctica and the U.S. Antarctic Program. Must interact in a professional manner with National Science Foundation staff, scientists and other USAP agencies and stakeholders. Additional Application Requirements: In addition to resume please submit the following: 3 examples of professionally published articles from your portfolio illustrating how a complex topic was distilled into an accurate and compelling article for the general public; 2 examples of an original graphic layout such as a brochure or flyer. PHYSICAL AND / OR OTHER SPECIFIC REQUIREMENTS: Deployment to Antarctica is required for this position. The individual in the position must successfully complete the physical and dental examinations as required by the NSF for deploying to Antarctica. Failure to meet these requirements may result in withdrawal of employment offer or other employment action. Applicant must be willing to deploy to Antarctica for 1-6 months annually (typically 3-4 months) based on business/program needs. Preferred Qualifications: A general understanding of the Internet, website layout, general multimedia production, and web content management applications is needed. This position does not create websites, but does need to place content into a content management application and work closely with the multi-media team. Driven by our talented workforce, the Integrated Missions Operation builds trust through an array of energy-related IT, environmental science and engineering solutions to meet our customers' needs. Key Programs and/or Capabilities: Antarctic Support Contract (ASC) Large Infrastructure Mission Support Digital Modernization Command & Control Mission Applications Science Energy and Environment Engineering Services Leidos is growing! Connect with us on LinkedIn and Facebook . We value and support the well-being and mobility of our employees with competitive benefit packages, complementary e-learning training, work-life flexibility, an exciting External Referral Program , and a diverse, inclusive and ethical work place. In fact, in 2020, Leidos was ranked as one of the "World's Most Ethical Companies" by the Ethisphere Institute for the third consecutive year. External Referral Bonus: Ineligible Potential for Telework: Yes, 25% Clearance Level Required: None Travel: Yes, 50% of the time Scheduled Weekly Hours: 40 Shift: Day Requisition Category: Professional Job Family: Writing and Editing Pay Range: Pay Range $48,750.00 - $75,000.00 - $101,250.00 Leidos is a Fortune 500 ® information technology, engineering, and science solutions and services leader working to solve the world's toughest challenges in the defense, intelligence, homeland security, civil, and health markets. The company's 38,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Va., Leidos reported annual revenues of approximately $11.09 billion for the fiscal year ended January 3, 2020. For more information, visit . Pay and benefits are fundamental to any career decision. That's why we craft compensation packages that reflect the importance of the work we do for our customers. Employment benefits include competitive compensation, Health and Wellness programs, Income Protection, Paid Leave and Retirement. More details are available here . Leidos will never ask you to provide payment-related information at any part of the employment application process. And Leidos will communicate with you only through emails that are sent from a Leidos.com email address. If you receive an email purporting to be from Leidos that asks for payment-related information or any other personal information, please report the email to . All qualified applicants will receive consideration for employment without regard to sex, race, ethnicity, age, national origin, citizenship, religion, physical or mental disability, medical condition, genetic information, pregnancy, family structure, marital status, ancestry, domestic partner status, sexual orientation, gender identity or expression, veteran or military status, or any other basis prohibited by law. Leidos will also consider for employment qualified applicants with criminal histories consistent with relevant laws.