Careers at Capital One

Senior Staff Full-stack Engineer - Customer Platforms As a Senior Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Senior Staff Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while delivering strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community. Senior Staff Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. The Team: In this role, you will be the technical lead for the Customer Management engineering organization, setting and delivering the technical agenda for the foundational platforms and horizontal thread teams (SRE, Sustained Engineering, Data, and Operations). You will manage the entire credit card customer lifecycle—from offer management to retention—to ensure a seamless and delightful experience. You will make credit decisioning & offers real time and intelligent, spanning dynamic credit offers, line, balance transfer, product upgrades, retention offers leveraging novel data sources and predictive models, as well as quantitative in-market testing and experimentation. You will drive an agenda to ship exponentially more products, experiences, and offers by arming cross-functional partners with GenAI tools, datasets, experimentation frameworks, and configurable/extensible systems that allow for self-service product delivery. All with one overarching goal: put more Capital One cards in more wallets. You will lead 100+ engineers across multiple directors, grow high-potential senior leaders, and even found a novel SRE function that raises operational excellence across the entire Customer Management domain. This is not a pure architecture role and you will work elbow-to-elbow with project teams coding, delivering, optimizing and operating the systems you design. The ideal candidate will excel at both surveying broad business domains, crafting a technical strategy to support the many possible futures of the business, and diving deep into the details and personally delivering the highest-leverage projects from that roadmap. What You’ll Do: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously, balancing your time to maximize impact Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Drive modernization of monolithic systems into microservice architectures and event-driven platforms Collaborate with senior engineering and architecture leaders to define long-term platform strategy and API standards Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers. Lead cross-divisional projects and impacts that promote technological best practices and enhancements Partner with product management to set an ambitious roadmap for expanding Capital One’s reach Partner with product management to set an ambitious roadmap for expanding Capital One’s reach. Hands-on full-stack coding (frontend, backend, data processing, automation) Lead the multi-year strategy to decommission legacy systems and converge the destination stack, reducing maintenance overhead and eliminating duplicative customer experiences across channels. Stand up and scale a hybrid SRE + Engineering Productivity function supporting the entire Acquisitions engineering org, achieving strong statistical process control and operational maturity. Design solutions that enable non-technical contributors to design, test, and deliver marketing experiments, UI treatments, and credit offers. Basic Qualifications: Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 9 years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture Preferred Qualifications: Master’s Degree in Computer Science or Software Engineering 12+ years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Web technologies (JavaScript, TypeScript and SPA frameworks) Designing and building distributed HPC and ML systems Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture 12+ years of professional experience coding in commonly used languages like Go, Java, JavaScript/TypeScript, Python, Rust, C#, Scala 10+ years of experience with database and database management systems 12+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support 10+ years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies 12+ years of experience with Networking protocols and integration with third party distributed systems 7+ years of experience mentoring senior engineers and driving professional development within technical teams 3+ years of experience leading cross-domain architectural reviews or establishing coding and design standards Expertise in the strategic application of agentic AI coding tools to solve systemic development challenges Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $286,200 - $326,700 for Sr. Staff Full-stack Engineer McLean, VA: $314,800 - $359,300 for Sr. Staff Full-stack Engineer Richmond, VA: $286,200 - $326,700 for Sr. Staff Full-stack Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).

Staff Full-stack Engineer - Global Payment Network As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Staff Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while delivering strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community. Staff Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. About the Team: The Global Payment Network (GPN) Technology organization designs, builds, and operates the mission-critical systems and infrastructure that seamlessly power complex money movement across domestic and international rails. We build and operate a high-volume, low-latency, and highly resilient distributed ecosystem that is simultaneously secure, performant, accurate, and nimble. As an engineer in the Global Payment Network, you will apply your technical acumen to shape and deliver solutions to complex problems at massive scale. You will engineer solutions across core network products, simplify global participant integration, and rapidly deliver new features. Leveraging automation and AI-native engineering, you will unlock real-time insights and advance our capabilities in domains ranging from high-throughput transaction processing to advanced fraud and risk mitigation. What You’ll Do: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously, balancing your time to maximize impact Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Drive modernization of monolithic systems into microservice architectures and event-driven platforms Collaborate with senior engineering and architecture leaders to define long-term platform strategy and API standards Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers. Lead cross-divisional projects and impacts that promote technological best practices and enhancements Basic Qualifications: Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 7 years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture Preferred Qualifications: Master’s Degree in Computer Science or Software Engineering 10+ years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Web technologies (JavaScript, TypeScript and SPA frameworks) Designing and building distributed HPC and ML systems Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture 10+ years of professional experience coding in commonly used languages like Go, Java, JavaScript/Typescript, Python, Rust, C#, Scala 8+ years of experience with database and database management systems 10+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support 8+ years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies 10+ years of experience with Networking protocols and integration with third party distributed systems 5+ years of experience mentoring senior engineers and driving professional development within technical teams 2+ years of experience leading cross-domain architectural reviews and establishing coding and design standards Expertise in the strategic application of agentic AI coding tools to solve systemic development challenges Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $244,700 - $279,200 for Staff Full-stack Engineer McLean, VA: $269,100 - $307,200 for Staff Full-stack Engineer Plano, TX: $244,700 - $279,200 for Staff Full-stack Engineer Riverwoods, IL: $244,700 - $279,200 for Staff Full-stack Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).

Staff Full-stack Engineer - Global Payment Network As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Staff Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while delivering strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community. Staff Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. About the Team: The Global Payment Network (GPN) Technology organization designs, builds, and operates the mission-critical systems and infrastructure that seamlessly power complex money movement across domestic and international rails. We build and operate a high-volume, low-latency, and highly resilient distributed ecosystem that is simultaneously secure, performant, accurate, and nimble. As an engineer in the Global Payment Network, you will apply your technical acumen to shape and deliver solutions to complex problems at massive scale. You will engineer solutions across core network products, simplify global participant integration, and rapidly deliver new features. Leveraging automation and AI-native engineering, you will unlock real-time insights and advance our capabilities in domains ranging from high-throughput transaction processing to advanced fraud and risk mitigation. What You’ll Do: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously, balancing your time to maximize impact Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Drive modernization of monolithic systems into microservice architectures and event-driven platforms Collaborate with senior engineering and architecture leaders to define long-term platform strategy and API standards Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers. Lead cross-divisional projects and impacts that promote technological best practices and enhancements Basic Qualifications: Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 7 years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture Preferred Qualifications: Master’s Degree in Computer Science or Software Engineering 10+ years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Web technologies (JavaScript, TypeScript and SPA frameworks) Designing and building distributed HPC and ML systems Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture 10+ years of professional experience coding in commonly used languages like Go, Java, JavaScript/Typescript, Python, Rust, C#, Scala 8+ years of experience with database and database management systems 10+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support 8+ years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies 10+ years of experience with Networking protocols and integration with third party distributed systems 5+ years of experience mentoring senior engineers and driving professional development within technical teams 2+ years of experience leading cross-domain architectural reviews and establishing coding and design standards Expertise in the strategic application of agentic AI coding tools to solve systemic development challenges Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $244,700 - $279,200 for Staff Full-stack Engineer McLean, VA: $269,100 - $307,200 for Staff Full-stack Engineer Plano, TX: $244,700 - $279,200 for Staff Full-stack Engineer Riverwoods, IL: $244,700 - $279,200 for Staff Full-stack Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).

Staff Full-stack Engineer - Global Payment Network As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Staff Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while delivering strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community. Staff Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. About the Team: The Global Payment Network (GPN) Technology organization designs, builds, and operates the mission-critical systems and infrastructure that seamlessly power complex money movement across domestic and international rails. We build and operate a high-volume, low-latency, and highly resilient distributed ecosystem that is simultaneously secure, performant, accurate, and nimble. As an engineer in the Global Payment Network, you will apply your technical acumen to shape and deliver solutions to complex problems at massive scale. You will engineer solutions across core network products, simplify global participant integration, and rapidly deliver new features. Leveraging automation and AI-native engineering, you will unlock real-time insights and advance our capabilities in domains ranging from high-throughput transaction processing to advanced fraud and risk mitigation. What You’ll Do: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously, balancing your time to maximize impact Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Drive modernization of monolithic systems into microservice architectures and event-driven platforms Collaborate with senior engineering and architecture leaders to define long-term platform strategy and API standards Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers. Lead cross-divisional projects and impacts that promote technological best practices and enhancements Basic Qualifications: Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 7 years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture Preferred Qualifications: Master’s Degree in Computer Science or Software Engineering 10+ years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Web technologies (JavaScript, TypeScript and SPA frameworks) Designing and building distributed HPC and ML systems Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture 10+ years of professional experience coding in commonly used languages like Go, Java, JavaScript/Typescript, Python, Rust, C#, Scala 8+ years of experience with database and database management systems 10+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support 8+ years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies 10+ years of experience with Networking protocols and integration with third party distributed systems 5+ years of experience mentoring senior engineers and driving professional development within technical teams 2+ years of experience leading cross-domain architectural reviews and establishing coding and design standards Expertise in the strategic application of agentic AI coding tools to solve systemic development challenges Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $244,700 - $279,200 for Staff Full-stack Engineer McLean, VA: $269,100 - $307,200 for Staff Full-stack Engineer Plano, TX: $244,700 - $279,200 for Staff Full-stack Engineer Riverwoods, IL: $244,700 - $279,200 for Staff Full-stack Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).

Staff Full-stack Engineer - Global Payment Network As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Staff Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while delivering strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community. Staff Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. About the Team: The Global Payment Network (GPN) Technology organization designs, builds, and operates the mission-critical systems and infrastructure that seamlessly power complex money movement across domestic and international rails. We build and operate a high-volume, low-latency, and highly resilient distributed ecosystem that is simultaneously secure, performant, accurate, and nimble. As an engineer in the Global Payment Network, you will apply your technical acumen to shape and deliver solutions to complex problems at massive scale. You will engineer solutions across core network products, simplify global participant integration, and rapidly deliver new features. Leveraging automation and AI-native engineering, you will unlock real-time insights and advance our capabilities in domains ranging from high-throughput transaction processing to advanced fraud and risk mitigation. What You’ll Do: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously, balancing your time to maximize impact Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Drive modernization of monolithic systems into microservice architectures and event-driven platforms Collaborate with senior engineering and architecture leaders to define long-term platform strategy and API standards Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers. Lead cross-divisional projects and impacts that promote technological best practices and enhancements Basic Qualifications: Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 7 years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture Preferred Qualifications: Master’s Degree in Computer Science or Software Engineering 10+ years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Web technologies (JavaScript, TypeScript and SPA frameworks) Designing and building distributed HPC and ML systems Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture 10+ years of professional experience coding in commonly used languages like Go, Java, JavaScript/Typescript, Python, Rust, C#, Scala 8+ years of experience with database and database management systems 10+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support 8+ years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies 10+ years of experience with Networking protocols and integration with third party distributed systems 5+ years of experience mentoring senior engineers and driving professional development within technical teams 2+ years of experience leading cross-domain architectural reviews and establishing coding and design standards Expertise in the strategic application of agentic AI coding tools to solve systemic development challenges Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $244,700 - $279,200 for Staff Full-stack Engineer McLean, VA: $269,100 - $307,200 for Staff Full-stack Engineer Plano, TX: $244,700 - $279,200 for Staff Full-stack Engineer Riverwoods, IL: $244,700 - $279,200 for Staff Full-stack Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You’ll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You’ll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You’ll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Senior Manager, Machine Learning Engineer Do you love building and pioneering in the AI and technology space? Do you enjoy solving complex business problems in a fast-paced, collaborative, inclusive, and iterative delivery environment? At Capital One, you'll be part of a big group of makers, breakers, doers and disruptors who love to solve real problems and meet real customer needs. We are seeking Machine Learning Engineers who are passionate about leveraging cutting-edge open source frameworks, advanced algorithms, and emerging technologies to join our team. As a Machine Learning Engineer, you’ll have the opportunity to be on the forefront of driving major AI transformations and scaling production models across Capital One. What You’ll Do: The MLE role overlaps with many disciplines, such as Ops, Modeling, and Data Engineering. In this role, you'll be expected to perform many ML engineering activities, including one or more of the following: Design, build, and/or deliver ML models and components that solve real-world business problems, while working in collaboration with the Product and Data Science teams Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale Inform your ML infrastructure decisions using your understanding of ML modeling techniques and issues, including choice of model, data, and feature selection, model training, hyperparameter tuning, dimensionality, bias/variance, and validation) Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment Collaborate as part of a cross-functional Agile team to create and enhance software that enables state-of-the-art big data and ML applications Retrain, maintain, and monitor models in production Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. Construct optimized data pipelines to feed ML models Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code Ensure all code is well-managed to reduce vulnerabilities, models are well-governed from a risk perspective, and the ML follows best practices in Responsible and Explainable AI Use programming languages like Python, Scala, or Java Basic Qualifications: Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 6 years of experience programming with Python, Java, Golang, or C++ At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data At least 4 years of experience deploying and operating Machine Learning solutions in production and operating production services in the cloud (AWS, GCP, Azure) and using Kubernetes to manage large scale containerized ML software systems Preferred Qualifications: Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field 5+ years of experience optimizing ML algorithms, configurations, and infrastructure 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. 5+ years of experience building resilient software solutions with pre-production testing, advanced deployment techniques (one-box, blue/green, gradual dial-up), monitoring, alarms, and preparing incident response plans 5+ years of experience working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) model types (Regression, Classification, Clustering, etc.), model Architectures (RNNs, CNNs, LSTMs, Transformers), training concepts (loss function, hyperparameters, regularization), and how to evaluate model accuracy and diagnose and address common issues (underfitting, overfitting) 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5 McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5 New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5 San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5 San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5 Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).

Staff Software Engineer - Card Tech As a Staff Engineer at Capital One, you will be part of a community of technical experts working to define the future of banking in the cloud. You will work alongside our talented team of developers, machine learning experts, product managers and people leaders. Our Staff Engineers are leading experts in their domains, helping devise practical and reusable solutions to complex problems. You will drive innovation at multiple levels, helping optimize business outcomes while delivering strong technology solutions. At Capital One, we believe diversity of thought strengthens our ability to influence, collaborate and provide the most innovative solutions across organizational boundaries. You will promote a culture of engineering excellence and strike the right balance between lending expertise and providing an inclusive environment where the ideas of others can be heard and championed. You will lead the way in creating next-generation talent for Capital One Tech, mentoring engineers and actively recruiting to keep building our community. Staff Engineers are expected to lead through technical contribution. You will operate as a trusted advisor for our key technologies, platforms and capability domains, creating clear and concise communications, code samples, blog posts and other materials to share knowledge both inside and outside the organization. You will specialize in a particular subject area, but your input and impact will be sought and expected throughout the organization. About the Team: Card Tech is seeking a Staff Engineer to join our team and fundamentally redefine the speed and quality of software development. We are a high-velocity, mission-driven group obsessed with bridging the gap between Intent and Execution (I=E). In this role, you won't just manage; you will operate as a "Player-Coach," functioning both as a high-leverage developer who ships production-ready code in hours as well as mentoring a team to become elite AI-native builders. You will own the technical benchmark, leveraging agentic development tools to its absolute limits through rigorous, spec-driven design to solve complex problems with unprecedented urgency. This leader must have the ability to attract top-tier talent and the technical "whisperer" skills to ensure AI-generated output is flawless, secure, and scalable. Success requires an innovative mind, a proven track record of delivering next-generation products, and a passion for AI-native execution. You are a master of technical specifications who can translate complex architectures into simple, actionable reality. If you are a high-agency leader ready to define the 100x engineer era and make a massive, visible impact on our company trajectory, this is your team. What You’ll Do: Articulate and evangelize a bold technical vision for your domain Decompose complex problems into practical and operational solutions Ensure the quality of technical design and implementation Serve as an authoritative expert on non-functional system characteristics, such as performance, scalability and operability Continue learning and injecting advanced technical knowledge into our community Handle several projects simultaneously, balancing your time to maximize impact Act as a role model and mentor within the tech community, helping to coach and strengthen the technical expertise and know-how of our engineering and product community Drive modernization of monolithic systems into microservice architectures and event-driven platforms Collaborate with senior engineering and architecture leaders to define long-term platform strategy and API standards Serve as a force-multiplier for the team, balancing deep, hands-on technical contribution and innovation with mentoring and elevating the skills of peers and junior engineers. Lead cross-divisional projects and impacts that promote technological best practices and enhancements Basic Qualifications: Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) At least 7 years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture Preferred Qualifications: Master’s Degree in Computer Science or Software Engineering 10+ years of experience in all of the following: Software engineering and solution architecture Enterprise architecture and design patterns Web technologies (JavaScript, TypeScript and SPA frameworks) Designing and building distributed HPC and ML systems Cloud computing (AWS, Microsoft Azure, Google Cloud) Data architecture 10+ years of professional experience coding in commonly used languages like Go, Java, JavaScript/Typescript, Python, Rust, C#, Scala 8+ years of experience with database and database management systems 10+ years of professional experience in the full lifecycle of system development, from conception through architecture, implementation, testing, deployment and production support 5+ years of experience with public cloud platforms (AWS, GCP, Azure), cloud-based productivity tools, or virtualization technologies 10+ years of experience with Networking protocols and integration with third party distributed systems 5+ years of experience mentoring senior engineers and driving professional development within technical teams 2+ years of experience leading cross-domain architectural reviews and establishing coding and design standards Expertise in the strategic application of agentic AI coding tools to solve systemic development challenges Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Chicago, IL: $244,700 - $279,200 for Staff Full-stack Engineer McLean, VA: $269,100 - $307,200 for Staff Full-stack Engineer New York, NY: $293,600 - $335,100 for Staff Full-stack Engineer Richmond, VA: $244,700 - $279,200 for Staff Full-stack Engineer San Francisco, CA: $293,600 - $335,100 for Staff Full-stack Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; 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 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com . 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 Careers@capitalone.com 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).