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Job DescriptionAbout Weee! Weee! is the largest and fastest-growing ethnic e-grocer in the United States, operating in one of the largest underserved categories in retail with affordable access to exciting ethnic food. By partnering with local suppliers, redesigning the value chain and leveraging social buying, Weee! is reshaping the grocery business entirely. You can read more about us on Business Insider, Reuters and TechCrunch. Weee! is headquartered in Fremont, CA, and is currently available coast to coast with exceptional growth (5x YoY) across geographies, categories and ethnicities. We have raised $800M+ in funding to date from leading investors including Softbank Vision Funds, DST, Blackstone, Tiger Global, Lightspeed Ventures, Goodwater Capital, XVC and iFly. The opportunity now is to join a rocketship as we prepare for the next stage of growth, and an eventual public listing. This role is part-time position in Clifton, NJ; Need someone to cover Thursday and Friday from 6pm to 6am. Refrigeration (Ammonia) System operators. Responsibilities: • Maintain the Ammonia refrigeration and other freon based cooling systems including, but not limited to operation, maintenance, and repairs., • Maintain and operate single, two stage, cascade ammonia systems and subsystems, • Monitor and identify abnormal operating pressures, temperatures, and conditions within the refrigeration system, adjust, repairs and/or schedule service as required, • Thoroughly understanding and able to handle refrigeration system components, including vacuum pumps, chillers, evaporators, condensers, compressors, controls, and valves etc., • Perform and delegate to daily, weekly, monthly, annually inspections, and preventative maintenance on the refrigeration equipment and other cooler machinery on and off-site as needed, • Perform other maintenance duties such as plumbing, replacing valves, installing fixtures, detecting, and repairing leaks as needed, • Handle hazardous materials as directed and follow guidance of OSHA and EPA, • Monitor and record all system readings to document operation of the equipment and the system and provide reports and troubleshooting, • Respond to emergency breakdowns of the refrigeration systems, • Procure quotations and bids for the order of work scopes, repairs, parts, and construction projects as needed, • Ensure continuous training and competency of refrigeration updates and standards, • Train personnel for routine check and system following the SOP, • Thoroughly understand and can act upon based on EAP and technical guidance during emergency and system malfunction situations, • Handle unscheduled and emergency shut down of equipment, • Ensure all refrigeration equipment is functioning in a safe and optimal manner, • Ensures continuous operation of all the facility utility systems and supports preventative maintenance programs., • Assists in the record-keeping and training requirements for all components of the Ammonia refrigeration system in compliance with State and federal guidelines., • Must perform duties as assigned by the facility Manager. & Chief Engineer Qualifications Must posses a Blue SealToxic To Operating license issued by the state of New Jersey • 5+ of Ammonia and freon based refrigeration experience, • 4+ years of active experience with cooling processes, ammonia refrigeration, and other freon based facilities within a produce and food processing and storage facility is a plus, • Experience with screw and reciprocating compressors, recirculation pumps, HVAC units, air compressors, and associated control systems, • Work experience in ammonia system pump-downs and repairs, • Knowledge of chemical testing for cooling towers and ammonia system preferred, • Strong electrical and mechanical troubleshooting skills, • Ability to understand refrigeration blueprints, P&ID, and cut sheets, • Hazmat Responder Certification preferred, • Trained and experienced in lock-out, tag-out, and safe work practices, • Must be able to respond to emergencies if needed 24/7 including after hours and weekends., • Best-practice and professional knowledge of industrial maintenance and standards, • Able to perform in a fast-paced environment, • Must be detailed-oriented, cost-conscious, and deadline sensitive Physical requirements • Able to climb stairs and ladders and fall-protection trained, • Able to work at variable heights, • Able to lift, push, and pull 50 lbs. in weight Environmental conditions • Roof height and outdoors; cold, wet, and cold storage temperatures Compensation Range • The US base hourly range for this full-time position is $37/hr - $43/hr, • This role may be eligible to discretionary bonus, incentives and benefits, • Our salary ranges are determined by role, level, and location The range displayed on each job posting reflects the minimum and maximum base salary for new hires for the position across all US locations. Within the range, individual pay is determined by multiple factors like job-related skills, experience and work locations. Your recruiter can share more about the specific salary range during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include any variable compensation elements. Weee! is an equal opportunity employer welcoming all qualified applicants regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status or any other basis prohibited by law. Discrimination or harassment of any kind is not tolerated at Weee!. If you need to inquire about an accommodation or need assistance with completing the application, please email us at applicantaccommodation@sayweee.com. For more jobs and to find out more about Weee!, visit our career page: https://about.sayweee.com/careers #INDWH Softbank Vision Funds California Employee Privacy Policy Intro/FAQ 3.19.2026 Weee! Privacy Policy for California Employees Applicants Contractors (March 2026)

AI Engineer 5 ((AI Foundations, LLM Core and Agentic AI)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Machine Learning Engineer 4 (Manager, IC)\n \n \n 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. \n \n What You’ll Do: \n\n • 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:\n, • 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\n, • 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)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • 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\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • 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\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • At least 2 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 Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ 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.\n, • 3+ 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)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n 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. \n Chicago, IL: $179,400 - $204,700 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description Kinsley Power Systems is seeking an Industrial Sales Engineer to add to their team! The Industrial Sales Engineer's main objective is to sell industrial power generation applications including related equipment (transfer switches, switchgear, load banks, fuel tanks, etc.) to end-users, engineers, electrical contractors, municipalities, government applications and OEMs, among others. Kinsley Power Systems, a family-owned business, has been an industry leader in generator service, sales and rentals for over 60 years. If you want to join a growing company with strong family values, a great culture, a company where you are valued for your hard work and have opportunities to grow – then look no further, come join our Kinsley family! Responsibilities: • Responsible for pursuing new project opportunities and closing sales, • Influences quote development, appropriate equipment and support services, project terms and conditions and ensuring customer support exists through the equipment warranty period, • Meets or exceeds quarterly sales quotas by driving sales with targeted customer types in identified verticals, as well as identifies opportunities with existing accounts in assigned territory, • Negotiates and closes deals which derive significant revenue and associated margins, • Understands the company's complete suite of products and services and identifies and hands-off cross-selling opportunities to other business verticals: residential equipment, rental agreements, prime power equipment, service contract sales, • Makes joint sales calls with appropriate technical/engineering sales resources - providing in-depth technical knowledge of the solutions we have to offer, • Develops long-term relationships with customer decision makers and influencers at the electrical contractor, engineer and building owner levels, • Maintains customer/project data in Customer Relationship Management software (CRM): Tracks active projects for weekly and monthly reporting, documenting of business development activity, and obstacles to success Preferred Skills and Experience: • Bachelor’s degree; or equivalent combination of education and experience will be considered on a case-by-case basis, • Proven passion and success in sales required, • Must be self-motivated with the ability to work independently and in a team atmosphere, • Possess a strong customer services focus with good verbal and written communication skills, • Must possess a strong sense of urgency and a proven ability to meet deadlines, • Proven competency in Microsoft Office, • Ability to work a flexible schedule, including overnight travel as required, • Possess and maintain a current, valid state driver’s license All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. The anticipated compensation range for this position is $85,000 to $130,000 annually. Actual compensation may vary based on skills, experience, certifications, location, and other business-related factors. Kinsley Group offers a comprehensive benefits package that may include medical, dental, and vision insurance, company-paid life insurance, disability coverage, paid time off, paid holidays, 401(k) with company match, employee assistance programs, and other company-sponsored benefits. Compensation details: 85000-130000 Yearly Salary PI344519d1c4b8-25405-39740032

Staff Fullstack Engineer \n \n We’re partnering with a fast-growing, Series B SaaS company in NYC building an AI-powered data and intelligence platform. They’re looking for a Staff Software Engineer to take technical ownership of critical product features, influence architecture, and help scale the engineering organization. \n \n Location: New York City - Hybrid, 4 days/week in office \n Type: Full-time \n What you’ll do \n\n • Own complex features and systems end-to-end, from architecture through production\n, • Build scalable, secure and well-tested applications and infrastructure\n, • Drive technical strategy and high-impact architectural improvements\n, • Work across frontend, backend, data and infrastructure as needed\n, • Partner closely with product and business teams to shape the roadmap\n, • Mentor engineers through technical leadership, code reviews and pair programming\n, • Improve engineering practices, performance and development processes\n\n \n Tech Stack \n Frontend: TypeScript, React, Node.js \n Backend: Python, Django, TypeScript, Node.js, MySQL/Postgres \n Data/Cloud: Snowflake, Dagster, AWS, GCP \n AI/Dev Tools: Cursor, Claude Code \n \n What we’re looking for \n\n • 7+ years software engineering experience, at least 1 year at staff level\n, • Strong hands-on experience with Python and/or TypeScript\n, • Proven experience owning and shipping complex, scalable applications\n, • Strong technical leadership and mentoring capabilities\n, • Experience using modern AI development tools\n

Machine Learning Engineer 5\n \n \n 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. \n \n What You’ll Do: \n\n • 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:\n, • 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\n, • Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale\n, • 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)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment\n, • 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\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code\n, • 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\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 6 years of experience programming with Python, Java, Golang, or C++\n, • At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • 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 Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 5+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 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\n, • 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)\n, • 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models\n, • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents\n, • Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n \n 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. \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n Plano, TX: $209,000 - $238,500 for Machine Learning Engineer 5\n \n Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (FM Hosting, LLM Inference)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (MLX, Agentic AI, Gen AI platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n \n Team Description: \n \n \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n \n What You’ll Do: \n \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n \n The Ideal Candidate: \n \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n \n Basic Qualifications: \n \n \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (AI Foundations, LLM Core and Agentic AI)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (AI Foundations, VLM Customization)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Machine Learning Engineer 5 (IC)\n \n \n 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. \n \n What You’ll Do: \n\n • 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:\n, • 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\n, • Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale\n, • 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)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment\n, • 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\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale.\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code\n, • 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\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 6 years of experience programming with Python, Java, Golang, or C++\n, • At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data\n, • 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 Machine Learning software systems\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 5+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 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\n, • 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)\n, • 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models\n, • 4+ years of on-the-job experience with an industry recognized ML framework such as Dask or XGboost.\n, • ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents\n, • Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n Richmond, VA: $209,000 - $238,500 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (Gen AI Platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (MLX, Agentic AI, Gen AI platform Services)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n \n \n Team Description: \n \n \n \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n \n \n What You’ll Do: \n \n \n \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n \n \n The Ideal Candidate: \n \n \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n \n \n Basic Qualifications: \n \n \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n \n \n Preferred Qualifications: \n \n \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (Vision model (VLM) customization experience)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Sr. Staff AI Engineer (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale\n, • Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide\n, • Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture\n, • Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership\n\n \n Capital One is open to hiring a Remote Employee for this opportunity. \n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies\n, • At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy\n, • 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership\n, • Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance\n, • Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams\n, • Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer\n \n Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 3 (AI Foundations)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Lead development and benchmarking of multi-turn conversational and tool-using agent workflows, ensuring measurable performance and safety metrics \n • \n Implement scalable pipelines for training, fine-tuning and deploying foundation or domain-specific models across multiple environments \n • \n Collaborate with research and data engineering teams to curate high-quality datasets and improve model evaluation methodologies \n • \n Contribute to governance and security efforts for model traceability, lineage documentation, and version control of deployed AI assets \n • \n Mentor junior AI engineers and advocate for engineering excellence, reproducibility, and responsible experimentation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 3 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 1 year of experience developing AI and ML algorithms or technologies \n • \n At least 3 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience contributing to development of components of AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 4 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Demonstrated ability to evaluate and optimize LLM performance using quantitative metrics (accuracy, coherence, latency, cost) \n • \n Hands-on experience implementing retrieval-augmented generation (RAG), vector database integrations, and fine-tuning workflows \n • \n Experience applying prompt-engineering strategies, safety guardrails, and red-teaming methodologies to production AI systems \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $161,800 - $184,600 for AI Engineer 3\n \n McLean, VA: $161,800 - $184,600 for AI Engineer 3\n \n New York, NY: $176,500 - $201,400 for AI Engineer 3\n \n San Jose, CA: $176,500 - $201,400 for AI Engineer 3\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Director AI Engineering (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n \n The Generative AI Training team builds the platform Capital One's scientists and engineers use to train, fine-tune, and experiment with foundation models at scale. We run the GPU clusters and distributed training infrastructure behind the company's generative AI: fair-share scheduling across teams, large-scale fine-tuning and reinforcement learning, resilience for long-running jobs, and the utilization controls that keep that expensive hardware working efficiently. We also provide the self-service environments where teams deploy, serve, and evaluate models during experimentation, built on tools like KServe and vLLM. The platform we build is a central leverage point for AI across Capital One, shaping how fast and how affordable the rest of the company can build with foundation models. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Oversee the design, development, testing, deployment, and operation of the platform's core systems: distributed training and fine-tuning, reinforcement learning workflows, fair-share GPU scheduling, job resilience and fault tolerance, GPU utilization and efficiency, and self-service environments for model experimentation and evaluation.\n, • Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art techniques to improve the scalability, cost, throughput, and reliability of large-scale distributed training and fine-tuning.\n, • Own GPU capacity planning and cost governance: right-size clusters, instance types, and quotas to the needs of training and experimentation workloads across teams.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI. \n, • Translate the enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline\n, • Scale AI engineering practices across teams through shared infrastructure, reusable components, and unified observability and governance frameworks\n, • Establish enterprise standard for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness\n, • Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Capital One is open to hiring a Remote Employee for this opportunity. \n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 3 years of people leadership experience\n\n \n Preferred Qualifications: \n\n • 5+ years of experience managing and leading an engineering team\n, • 7+ years of experience building and operating large-scale ML or GPU training infrastructure on cloud platforms (e.g., AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Hands-on experience with distributed training at scale: multi-node, multi-GPU jobs and parallelism strategies (e.g., PyTorch FSDP, DeepSpeed, Megatron), with proficiency in Python, Go, C++, or CUDA\n, • Experience with the ML orchestration and scheduling stack (e.g., Kubernetes, Kubeflow, Kueue, Slurm, Ray, KServe, vLLM)\n, • Experience operating large GPU fleets with a focus on reliability, fault tolerance, utilization, and cost efficiency\n, • Experience right-sizing GPU clusters, instance types, interconnect, and quotas to training and experimentation workload requirements (e.g., model size, parallelism strategy, throughput targets)\n, • Passion for staying abreast of the latest AI and ML-systems research, and judiciously applying novel training and optimization techniques\n, • Excellent communication and presentation skills, with the ability to articulate complex AI and infrastructure concepts to peers\n, • Experience building and leading a multi-team AI organization delivering multiple enterprise capabilities concurrently\n, • Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks\n, • Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineer\n \n Cambridge, MA: $269,100 - $307,200 for Director, AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Director, AI Engineer\n \n New York, NY: $293,600 - $335,100 for Director, AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Director, AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Director, AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluations)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (Gen AI Platform Services - Agentic AI)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (Gen AI Platform Services - Agentic Systems)\n \n \n Overview: \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems\n, • Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency\n, • Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards\n, • Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies\n, • At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 7+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting complex AI systems\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines\n, • Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes\n, • Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Sr. Manager, AI Engineer (IFX)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One \n • \n Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One \n • \n Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI \n • \n Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts \n • \n Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems \n • \n Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 1 year of people leadership experience \n\n \n Preferred Qualifications: \n\n • \n 3 years of experience managing and leading an engineering team \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery \n • \n Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance \n • \n Track record mentoring engineers/scientists to productize prototypes and meet production SLOs \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Machine Learning Engineer 4 - Intelligent Foundations and Experiences (IFX)\n \n \n 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. \n \n What You’ll Do: \n\n • 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:\n, • 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\n, • 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)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • 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\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • 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\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data\n, • At least 2 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\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ 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.\n, • 3+ 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)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n 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. \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Sr. Manager, AI Engineer (Gen AI Platform Services: Agentic AI, Guardrails, Evaluation)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One \n • \n Oversee the design, development, testing, deployment, and support AI software components including foundation model training, large language model inference, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Make high judgment build-vs-buy decisions across a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One \n • \n Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI \n • \n Translate enterprise AI goals into actionable team roadmaps with measurable outcomes and regular readouts \n • \n Operationalize Responsible AI: establish review gates, documentation/evaluation requirements, and rollout/rollback standards for all production AI systems \n • \n Create strong collaboration interfaces with Research, Data, and Platform teams to accelerate model lifecycle \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 1 year of people leadership experience \n\n \n Preferred Qualifications: \n\n • \n 3 years of experience managing and leading an engineering team \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience leading technical strategy for a multi-disciplinary AI team, balancing research exploration with production delivery \n • \n Familiarity with MLOps, AI observability (evaluation pipelines, drift monitoring, model/version governance) to ensure reliability and compliance \n • \n Track record mentoring engineers/scientists to productize prototypes and meet production SLOs \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n McLean, VA: $229,900 - $262,400 for Sr. Manager, AI Engineer\n \n New York, NY: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Francisco, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n San Jose, CA: $250,800 - $286,200 for Sr. Manager, AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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 AI Engineer\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams\n, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads\n, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design\n, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 8 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks\n, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency\n, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization\n, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility \n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n ion. \n \n 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. \n Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Staff AI Engineer\n \n New York, NY: $293,600 - $335,100 for Staff AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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\n \n \n 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. \n \n What You’ll Do: \n\n • \n 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: \n • \n 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 \n • \n Build and scale massive multi-tenant platforms that enable running large footprint ML model training and/or serving at scale \n • \n 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) \n • \n Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n • \n 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 \n • \n Retrain, maintain, and monitor models in production \n • \n Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale. \n • \n Construct optimized data pipelines to feed ML models \n • \n Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n • \n 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 \n • \n Use programming languages like Python, Scala, or Java \n\n \n Basic Qualifications: \n\n • \n Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering) \n • \n At least 6 years of experience programming with Python, Java, Golang, or C++ \n • \n At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn) \n • \n At least 6 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data \n • \n 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 \n\n \n Preferred Qualifications: \n\n • \n Master's or doctoral degree in computer science, electrical engineering, mathematics, or related field \n • \n 5+ years of experience optimizing ML algorithms, configurations, and infrastructure \n • \n 5+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n • \n 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 \n • \n 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) \n • \n 5+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models \n • \n ML industry impact through conference presentations, papers, blog posts, open source contributions, or patents \n • \n Ability to communicate complex technical and machine learning concepts clearly to a variety of audiences \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n McLean, VA: $229,900 - $262,400 for Machine Learning Engineer 5\n \n New York, NY: $250,800 - $286,200 for Machine Learning Engineer 5\n \n San Francisco, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for Machine Learning Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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 Staff AI Engineer - Agentic AI Platform (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n Capital One is open to hiring a Remote Employee for this opportunity \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Define and steer the technical AI architecture vision, integrating applied research breakthroughs into production ecosystems with reliability and scale\n, • Lead the establishment of AI performance, safety, and transparency standards that guide all model development and deployment company-wide\n, • Drive multi-year platform initiatives that unify data, compute and model lifecycle management under and cohesive enterprise AI architecture\n, • Mentor senior technical leaders across research, data and engineering disciplines, developing the next generation of Capital One’s AI technical leadership\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 10 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies\n, • At least 10 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience architecting AI platforms with tradeoff decisions around cost, latency, throughput and accuracy\n, • 9+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the SVP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Recognized industry leader in applied AI or machine learning infrastructure through patents, publications, or open-source leadership\n, • Demonstrated experience designing long-term AI infrastructure strategies - balancing cost, scale, ethics and regulatory compliance\n, • Experience driving organization-wide adoption of AI safety, alignment and governance standards, collaborating with policy, risk and legal teams\n, • Proven ability to shape R&D investment strategy by identifying breakthrough AI capabilities with material business impact\n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Remote (Regardless of Location): $286,200 - $326,700 for Sr. Staff AI Engineer\n \n Cambridge, MA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n McLean, VA: $314,800 - $359,300 for Sr. Staff AI Engineer\n \n New York, NY: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Francisco, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n San Jose, CA: $343,400 - $392,000 for Sr. Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (AI Foundations, VLM Customization)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

\n Are you inspired by the idea of supporting our nation’s critical infrastructure and securing communications for first responders, utilities, and transportation?\n\n\n\n\n Are you a top-performer with experience in managing channel partners while also taking a lead in developing business to support channel partners year-over-year growth?\n\n\n\n\n Are you interested in being part of a fast-paced, growing company with opportunities to expand your knowledge base across a multitude of mission critical communications technologies and product lines?\n\n\n\n\n Company Overview\n\n\n Eastern Communications, Ltd. is a critical communications provider based in Long Island City, Queens, NY. Founded in 1976, and acquired from original ownership in 2020, Eastern provides infrastructure, technical services, field replacement parts, and maintenance to a range of end users including public safety, transportation, utilities, and the federal government.\n\n\n\n\n For more than 50 years, Eastern has built a reputation for technical excellence, innovation, and exceptional customer service. Strategic acquisitions of RACOM Corporation in 2023, PMC in 2025, and most recently, GenComm in 2026, have expanded our capabilities and geographic reach, creating one of the largest mission-critical communications providers in the United States. Today, Eastern partners with industry-leading manufacturers to design, deploy, and support communications systems that help keep first responders, critical infrastructure, and communities connected when it matters most. \n\n\n\n\n Role Overview\n\n\n With the continued growth of the company, we are currently looking for a Staff Solutions Engineer to provide technical pre-sales support on radio communications system opportunities for Public Safety, Industrial, Transportation and Utility markets. This Staff Solutions Engineer will serve as the trusted technical advisor for Eastern's Dealer Channel, partnering with Regional Channel Managers to develop winning technical strategies and deliver industry-leading communications solutions.\n\n\n\n\n The ideal candidate combines deep technical expertise with strong customer engagement skills and enjoys solving difficult engineering problems, learning new technologies, collaborating across disciplines, and translating complex technical concepts into practical solutions.\n\n\nDuties and Responsibilities Include but are not limited to:\n\n Sales & Customer Engagement \n \n • Partner with Regional Channel Managers to develop technical sales strategies.\n, • Serve as a trusted technical advisor throughout the sales cycle.\n, • Deliver technical presentations, product demonstrations, and solution workshops to drive sales enablement.\n \n Solution Design \n \n • Develop integrated solutions using P25, DMR, LTE/FirstNet, microwave, dispatch consoles, IP networking, and related technologies.\n, • Develop quotations, Bills of Material (BOMs), system drawings, and technical documentation.\n, • Perform RF propagation studies and coverage analysis.\n, • Provide technical support to Dealers in responses for RFPs, ensuring compliant, competitive, and compelling submissions.\n \n Technical Leadership \n \n • Research and respond to technical inquiries across various vendor product lines.\n, • Stay current on emerging communications technologies and vendor product portfolios.\n, • Provide technical sales training to our Dealers on new products, engineering tools, and best practices.\n \nPosition Requirements\n\n \n, • Bachelor’s degree in Engineering or equivalent experience.\n, • 5+ years in a pre-sales or system engineering role.\n, • Proven experience providing customer-facing technical pre-sales support, solution design, and engineering consultation through direct customer and Dealer engagements.\n, • Demonstrated ability to solve complex engineering challenges through sound technical judgment, continuous learning, and innovative solution design.\n, • Proficiency with Microsoft Office, including Excel, Word, PowerPoint, and Visio.\n \nPreferred Qualifications:\n\n \n, • Experience designing mission-critical communications systems utilizing P25 and DMR conventional and trunked radio systems, microwave backhaul, and dispatch console platforms.\n, • Experience with engineering software used for RF propagation modeling, in-building wireless (DAS) design, and microwave path analysis, including tools such as RAPTR, EDX SignalPro, IBwave, Pathloss, or equivalent platforms.\n, • Experience using AI productivity tools (e.g., Microsoft Copilot, ChatGPT, Claude, or similar) to improve engineering, proposal development, technical writing, and workflow efficiency.\n \nLocation & Travel:\n\n \n, • Remote (Eastern or Central Time Zone).\n, • Located within approximately 50 miles from a major airport.\n, • Approximately 25% travel.\n \n\n\n Expected Salary Range does not include annual performance-based bonus or benefits package.\n\n \n$110,000 - $130,000 a year\n \n \n \n Compensation details: 110000-130000 Yearly Salary \n \n \n \n \n PI72c9d5881a55-25405-41563925

AI Engineer 4 (Gen AI Platform Services: Agentic AI, Agent Guardrails, Agent Evaluation, Agent Memory)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 5 (GenAI Platform Services, Agentic Platform)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Design, implement and optimize multi-model orchestration pipelines - integrating LLMs, vector search, and domain-specific models into unified systems \n • \n Establish and lead cost-performance governance reviews across AI systems, tracking GPU utilization, model throughput, and inference cost efficiency \n • \n Lead team design councils or design review boards to ensure technical consistency and compliance with AI engineering standards \n • \n Mentor Principal and Manager-level AI engineers, fostering cross-domain learning and elevating organizational technical maturity \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies \n • \n At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 7 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting complex AI systems \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers \n • \n Experience architecting and integrating heterogeneous AI systems - including rule-based, retrieval-augmented, and generative components - into unified production pipelines \n • \n Experience defining and enforcing standards for ethical AI deployment, including explainability, fairness, and human-in-the-loop review processes \n • \n Demonstrated ability to balance model performance and operational cost through dynamic inference strategies and model compression \n • \n Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs) \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $229,900 - $262,400 for AI Engineer 5\n \n McLean, VA: $229,900 - $262,400 for AI Engineer 5\n \n New York, NY: $250,800 - $286,200 for AI Engineer 5\n \n San Jose, CA: $250,800 - $286,200 for AI Engineer 5\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

Founding Engineer About Atmos Clinic Atmos Clinic is a seed-stage healthcare startup based in New York City, building a new way for everyday Americans to access and pay for healthcare. We recently raised $6 million from Define Ventures, Next Ventures, Tau Ventures, and leading health-tech founders and CEOs, giving us the backing to build an ambitious company for the long term. Atmos was started by a team of repeat founders who have built clinical AI, modern health benefits, and care delivery products at companies including Ambience Healthcare and Oscar Health. We're combining those experiences to close a widening gap: small-business health insurance premiums are rising 15%+ year over year while wages barely move. More than a third of covered workers face deductibles above $3,000 before their insurance actually kicks in, and an estimated 65 million workers are left without meaningful access to everyday care. The health insurance system is broken and we’re building an alternative layer on top. Atmos Clinic is an AI-native care platform that combines 1) chat-based advanced virtual primary care, 2) an employer-sponsored healthcare expense card, and 3) a marketplace of transparently priced local healthcare services. Employers can switch to more affordable health insurance plans and use the savings to offer Atmos Clinic on top, finally giving their employees a better healthcare experience at a lower cost. We want Atmos to feel nothing like a traditional healthcare product. Talk to it like ChatGPT. Find care like Airbnb. Spend like Ramp. We’re building a world-class consumer experience and pushing the boundaries of interaction and visual design, drawing inspiration from products like HeyClicky, Wispr Flow and Partiful. The goal isn't just to make healthcare work better, but to make it feel simpler, more intuitive, and more delightful to use. The Role We are hiring a Founding Engineer to help build Atmos from early prototypes through launch and scale. This is a full-stack role with a particular emphasis on frontend craft and design judgment. You’ll turn complex healthcare workflows into simple, intuitive experiences, then build the APIs, data models, and integrations that make them work. You’ll have real ownership over architecture, product decisions, interaction design, and implementation. You’ll work directly with the founders and a small technical team, make decisions without layers of process, and see your choices show up in the product quickly. You’ll help shape our technical foundation and design system, and over time help build the team around them. Our member experience will span web and mobile. Prior mobile experience is a plus; what matters most is strong full-stack engineering, an eye for design, and the ability to learn new tools quickly. What You’ll Do • Turn early product ideas into polished user flows and working software, making thoughtful calls on layout, visual hierarchy, copy, and interaction details as you build., • Build across the stack, from responsive frontend interfaces to backend services, data models, and third-party integrations. Shape the experiences that connect members, clinicians, employers, and providers across care, payments, and the marketplace., • Create thoughtful interactions for AI-native care, including real-time responses, voice and multimodal input, care threads, and healthcare payments. Bring a high bar for motion, latency, accessibility, and loading, empty, and error states across web and mobile., • Own features from interface to production: API design and integration, authentication, secure handling of sensitive data, testing, observability, deployment, and ongoing maintenance. Get up to speed on our mobile tooling and help own app releases, including App Store and Play Store submissions., • Ship quickly, talk to users, study how the product behaves in the real world, and iterate from feedback and usage data., • Help set product priorities directly with the founders. Choose tools, establish practical engineering standards and reusable UI components, and help recruit the engineering team around the product you created. What Success Looks Like • In your first six months, ship core product experiences from prototype through launch, with real users relying on the interfaces and underlying systems you built., • Create a consumer experience that feels simple, intuitive, and delightful, and establish a high bar for visual design and product craft across the company., • Establish a technical foundation, reusable UI components, and testing, monitoring, and release practices that let a small team move quickly while maintaining reliability., • Become a trusted owner of major product areas across the stack, build confidence shipping across web and mobile, and help define the next phase of the roadmap and engineering team. Who You Are Must-haves • You have several years of experience on a strong engineering team and have personally shipped and maintained meaningful full-stack features or products. You can take a feature from the user interface through backend implementation and into production., • You want broader ownership than a large team can usually offer. You’re comfortable taking an ambiguous problem, deciding what should be built, and carrying it through to a polished product., • You’re strong in modern frontend development and comfortable building backend services, APIs, and data models. You have solid fundamentals in authentication, debugging, testing, performance, and production reliability., • You use AI development tools aggressively but thoughtfully to ship faster and learn unfamiliar parts of the stack. You can explain, review, test, and maintain the code they help produce., • You have a strong eye for design and care about product craft as much as code quality. You can point to work that shows thoughtful visual hierarchy, typography, spacing, and interaction design. You notice latency, motion, edge cases, and copy, and can make good UX decisions without a detailed spec for every screen., • You work independently, move quickly without being sloppy, communicate risks early, and enjoy direct feedback and high-context collaboration. Nice-to-haves • Experience building a product from the first version, or a strong desire to move from a larger company into a true zero-to-one environment., • Mobile development experience, especially with React Native or another framework for shared iOS and Android code, and familiarity with app-store submissions and release cycles., • Experience building consumer products with polished onboarding, animation, or conversational interfaces, or creating a reusable component library or design system., • Experience with healthcare, fintech, AI products, or other applications that handle sensitive information and high-trust user journeys. Practical Details • Location: New York City. We work together in person (~3 days/wk)., • Employment: Full-time, with respect for work-life balance., • Compensation: $180,000–$240,000 annual base salary, depending on experience, plus meaningful founding equity (0.5% – 1%+) reflecting the ownership and impact of the role., • Benefits: general startup offerings including health insurance, 401k, etc.

Job Description Job Title: AI Engineer Location: New York, NY Department: Technology/Revenue Strategy Reports To: Chief Executive Officer FLSA Status: Exempt Work Type: Remote Position with occasional travel to the Corporate Office Employment Type: Full Time Company: Rebel Hotel Company About Rebel Hotel Company: Rebel Hotel Company is one of the fastest-growing third-party hotel management companies in the United States, recognized for delivering bold results, operational excellence, and distinctive guest experiences. We operate a diverse portfolio of full-service, lifestyle, and branded hotels across major metropolitan and resort markets. We are building a culture of leadership, innovation, and accountability—and we’re just getting started. Position Summary: We're a hospitality company building the next generation of intelligent pricing, demand, and guest-experience systems. Today our commercial teams run rate strategy, RFP negotiations, and account planning on spreadsheets and intuition. We're hiring an AI Engineer to turn that work into software — models and tools that forecast demand, optimize rates, and surface account intelligence so our revenue managers make sharper decisions, faster. This is a hands-on engineering role with direct line of sight to revenue. You'll work alongside revenue managers, sales leaders, and data analysts, shipping production systems that touch real pricing and booking decisions across our portfolio. What You'll Build • Demand forecasting models that predict occupancy and room-night demand by property, segment, day-of-week, and season — accounting for events, seasonality, and booking pace., • Dynamic pricing and rate-optimization engines that recommend BAR and corporate rates, balancing occupancy, ADR, and RevPAR against competitor positioning., • Account intelligence tooling that ingests internal production data and external signals (M&A activity, headcount trends, travel-budget shifts) to flag growing accounts, at-risk accounts, and uncaptured market opportunity., • Labor and staffing models that forecast labor demand against projected occupancy and arrivals — optimizing schedules, hours, and cost across housekeeping, front desk, F&B, and other departments while protecting service levels., • RFP and negotiation support tools that help the team price contracts, model rate scenarios, and prioritize target accounts during RFP season., • LLM-powered workflows — summarizing market intelligence, drafting account strategy notes, and answering natural-language questions over revenue data., • A testing laboratory for beta technologies — stand up and run a controlled environment where new AI tools and models can be piloted, stress-tested, and validated against real operational data before broader rollout, including the experimentation framework, sandboxed data, and feedback loops with property and commercial teams What You'll Do • Design, train, evaluate, and deploy machine learning models on real booking, rate, and market data., • Build data pipelines that bring together PMS, CRS, booking-channel, and third-party market data into clean, reliable feature sets., • Stand up the infrastructure to serve models in production — APIs, monitoring, retraining, and guardrails., • Operate the beta testing lab — design pilots, recruit internal users, measure results, and decide what graduates to production versus what gets killed., • Partner closely with revenue and commercial teams to translate domain knowledge into product, and to make sure outputs are trustworthy and actionable., • Define and track the metrics that matter — forecast accuracy, recommendation adoption, labor cost and productivity, and downstream revenue impact. What We’re Looking For Required • 3+ years building and shipping ML systems in production (not just notebooks)., • Strong Python and the modern ML/data stack (e.g. pandas, scikit-learn, PyTorch or TensorFlow, SQL)., • Solid grounding in forecasting, optimization, or recommendation/pricing problems., • Experience taking models from prototype to deployed service, including monitoring and iteration., • Ability to communicate clearly with non-technical stakeholders and translate business problems into technical ones. Nice to have • Experience in hospitality, travel, airlines, retail, or another revenue-management-driven industry., • Familiarity with dynamic pricing, demand modeling, or yield/revenue management., • Experience integrating LLMs into applications (RAG, structured extraction, agentic workflows)., • Cloud and MLOps experience (AWS/GCP/Azure, containerization, CI/CD for ML)., • Comfort with experimentation and causal measurement (A/B testing, uplift modeling). What We Offer: • Competitive base salary and performance-based incentive plan, • Medical, dental, and vision insurance, • 401(k) plan with company match, • Paid time off and holidays, • Career advancement opportunities within a rapidly growing company, • A chance to be part of the Rebel movement redefining hospitality leadership Why This Role You'll own meaningful problems end-to-end, see your work move real revenue, and help build a data and AI capability from an early stage. If you want your models to ship and matter rather than sit in a backlog, this is that role. Salary Range: $190,000 - $200,000 annually At Rebel Hotel Company, we don’t manage hotels the old way—we challenge the status quo. If you’re ready to lead with vision, act with ownership, and make your mark in the hospitality world, we want to meet you.

Job Description Hotel Maintenance Technician (Line Engineer) SUMMARY: The Line Engineer I supports the day-to-day maintenance of the hotel by performing basic repairs and preventative maintenance tasks. This entry-level role provides foundational experience in facilities operations and focuses on supporting guest comfort and safety. RESPONSIBILITIES: Maintenance & Repair · Assist with maintenance and repair of plumbing, electrical, HVAC, and guestroom systems under supervision. · Respond to routine service calls in a timely and guest-friendly manner. · Complete light tasks including bulb replacement, minor drywall repair, touch-up painting, and filter changes. · Assist in troubleshooting maintenance issues and identifying root causes. Inspections & Documentation · Perform daily inspections and document findings for guest rooms, public areas, and equipment. · Maintain detailed logs and records of maintenance activity. · Maintain accurate records of completed work, project updates, and equipment status in designated logs or software. · Log daily activities, work orders, and shift issues to support effective team communication. Safety & Compliance · Learn and follow company safety procedures including Lockout/Tagout and PPE usage. · Maintain current knowledge of applicable federal, state, and local building codes and regulations. · Comply with all departmental safety procedures and support an accident-free work environment. · Identify and immediately address any unsafe or hazardous conditions affecting guests or employees. · Reference and adhere to company Standard Operating Procedures (SOPs) as part of daily operations. Emergency Response · Assist in monitoring facility systems and responding to malfunctions or emergencies in a timely, effective manner. · Respond to building emergencies and act quickly to protect guests, staff, and assets. · Restore systems to normal operations efficiently after disruptions or emergency incidents. Tools, Equipment & Work Areas · Keep maintenance areas and equipment organized and clean. · Ensure tools and maintenance areas are safe, secure, and organized. · Clean, lubricate, and maintain tools and equipment; ensure proper storage after use. · Safeguard assigned tool pouch and equipment in accordance with engineering department standards. · Maintain cleanliness and organization in all engineering and maintenance work areas. Communication & Professionalism · Report to work on time and in full uniform, and uphold a professional appearance and conduct in all guest and team interactions. · Communicate with engineering management regarding work status, required materials, and delayed tasks. · Comply with all policies in the M&R Employee Handbook and perform additional duties as assigned by management. Qualifications · High school diploma or equivalent preferred. · 0-1 year of general maintenance or facilities experience preferred. · Basic mechanical aptitude and familiarity with tools. · Willingness to learn and follow instructions. Physical Requirements This role requires the ability to lift up to 50 lbs, climb ladders, and perform physically demanding tasks throughout the shift. The Line Engineer I must be able to work a flexible schedule including nights, weekends, and holidays as business needs require. M&R Hotel Management is committed to equal employment opportunity. Qualified individuals must be able to perform the essential functions of the position, with or without reasonable accommodation. Associates or applicants who require a reasonable accommodation should contact the People & Culture Department. Employment Eligibility Verification M&R Hotel Management participates in the federal E-Verify program. All offers of employment are contingent upon successful completion of the Form I-9 employment eligibility verification process and confirmation of authorization to work in the United States.

About Us Surgeon Decision Intelligence (SDI) is an emerging leader in AI-driven medical imaging solutions for orthopedic care. Founded by a team of orthopedic spine surgeons and medical students from the Hospital for Special Surgery, the world’s best orthopedic hospital, our mission is to transform patient care by developing quantitative imaging biomarkers to inform treatment approaches for a broad spectrum of musculoskeletal disease and predict associated outcomes. We combine cutting-edge computer vision, medical image analysis, and machine learning to unlock new insights from MRI imaging, one of the most widely obtained modalities of medical imaging, accelerating the translation of novel imaging biomarkers from research into clinical practice. Our team is passionate about bridging the gap between advanced computational methods and real-world healthcare impact. Position Summary The Principal Software Quality Engineer is responsible for leading software quality assurance activities for our Class II AI/ML-based Software as a Medical Device (SaMD). This role provides technical leadership and quality oversight across the full software lifecycle, including design controls, risk management, verification and validation, cybersecurity, release management, post-market activities, change control, and quality system compliance. You will work closely with Software Engineering, Machine Learning, Product, Regulatory, Clinical, and Cybersecurity teams to ensure our software is developed, tested, released, maintained, and changed in a controlled, compliant, and risk-based manner that supports product safety, effectiveness, and quality, including Quality System requirements. You will also provide technical oversight, mentoring, and review of work performed by internal teams, consultants, contractors, and third-party service providers. Essential Responsibilities: The Principal Software Quality Engineer is responsible for supporting and leading software quality activities across the full product lifecycle, including design, development, verification, validation, release, maintenance, and post-market change control. Essential responsibilities include, but are not limited to, the following: · Provide software quality engineering leadership for the Company’s Class II AI/ML-based Software as a Medical Device. · Support compliance with applicable medical device software regulations, standards, guidance documents, and internal quality system procedures. · Provide Quality oversight for software lifecycle activities, including requirements, design, development, verification, validation, release, maintenance, and change control. · Review and approve software quality documentation, including software requirements, design documentation, risk analyses, cybersecurity risk analyses, traceability matrices, verification protocols, validation protocols, test reports, release documentation, and change records. · Ensure software requirements are clear, testable, traceable, risk-based, and aligned with user needs and intended use. · Support design control activities, including design inputs, design outputs, design reviews, design verification, design validation, design transfer, and design changes. · Ensure appropriate traceability among requirements, design outputs, risk controls, verification testing, validation testing, defects, and released software. · Provide quality oversight for AI/ML-related software activities, including algorithm performance documentation, dataset considerations, acceptance criteria, validation activities, and change impact assessments. · Support software verification and validation activities, including test plans, test cases, automated testing, regression testing, performance testing, cybersecurity testing, deviations, anomalies, and final reports. · Evaluate software defects, deviations, and unresolved anomalies for safety, performance, cybersecurity, regulatory, and release impact. · Support software release readiness reviews and confirm required testing, documentation, risk assessments, cybersecurity activities, and approvals are complete. · Review and approve software change requests and impact assessments, including impact to requirements, risk management, cybersecurity, validation, labeling, and regulatory documentation. · Provide quality oversight for cloud-based software deployment, configuration management, access controls, release controls, CI/CD processes, source code repositories, and software development tools. · Support cybersecurity quality activities, including review of threat models, vulnerability assessments, penetration testing results, SBOM documentation, vulnerability dispositions, and cybersecurity risk mitigations. · Support supplier quality activities for software-related suppliers, cloud service providers, software development contractors, cybersecurity vendors, and other third-party service providers. · Support post-market software quality activities, including complaint investigations, CAPA, nonconformances, field issues, software patches, and maintenance releases. · Provide quality input for regulatory submissions and responses to regulatory questions related to software, cybersecurity, risk management, and verification and validation. · Participate in internal audits, external audits, supplier audits, and regulatory inspections related to software quality and SaMD development. · Identify and support improvements to software quality processes, design controls, risk management, verification and validation, cybersecurity, and release management. · Mentor cross-functional team members on software quality expectations, documentation practices, risk-based thinking, and medical device software compliance. · Oversee our cloud infrastructure (Azure/AWS), CI/CD pipelines, and DevSecOps practices. Minimum Qualifications: To be qualified for this role, the Principal Software Quality Engineer shall meet the following requirements: · Bachelor’s degree in Software Engineering, Computer Science, Biomedical Engineering, Electrical Engineering, Systems Engineering, or a related technical discipline. · Minimum of 8 years of experience in software quality engineering, software development, software verification and validation, quality engineering, or related medical device software role. · Minimum of 5 years of experience working in a regulated medical device, SaMD, digital health, diagnostic imaging, healthcare software, or other regulated life sciences environment. · Demonstrated knowledge of medical device design controls and software lifecycle requirements. · Demonstrated knowledge of the US FDA’s expectations for maintaining AI/ML-enabled medical devices including predetermined change control plans, real-world performance monitoring, and algorithm change management. · Experience with software verification and validation, including review of test plans, protocols, test cases, test results, deviations, anomalies, and traceability. · Experience with risk management for medical devices, including hazard analysis, software risk analysis, cybersecurity risk analysis, and risk control verification. · Working knowledge of applicable standards and regulations, such as 21 CFR Part 820, ISO 13485, ISO 14971, IEC 62304, IEC 62366-1, and FDA guidance for medical device software. · Experience supporting software change control, release readiness, configuration management, and defect management. · Experience working with cross-functional teams, including software engineering, product, regulatory, clinical, cybersecurity, and quality. · Strong technical writing skills, including ability to write and review clear, complete, and audit-ready quality records. · Strong analytical and problem-solving skills, including ability to assess technical issues for quality, safety, cybersecurity, regulatory, and business impact. · Ability to work independently, prioritize work, and provide technical leadership in a fast-paced development environment. · Proficiency in English, including ability to read, write, review, and approve technical and quality documentation. Preferred qualifications include: · Master’s degree in Software Engineering, Computer Science, Biomedical Engineering, Regulatory Science, Quality Assurance, or a related discipline. · Experience with AI/ML-enabled medical devices, imaging software, quantitative imaging biomarkers, radiology workflows, MRI image processing, or clinical decision-support software. · Experience with Class II SaMD regulatory submissions, including US FDA 510(k) submissions. · Experience with cloud-based software platforms and Microsoft Azure. · Experience with cybersecurity documentation for medical devices, including threat modeling, SBOM review, vulnerability assessment, penetration testing, and cybersecurity risk management. · Experience with automated testing frameworks, CI/CD pipelines, DevOps practices, GitHub, Jira, Azure DevOps, or similar tools. · Experience with software tool validation or computer software assurance. · Experience supporting US FDA inspections, ISO 13485 audits, MDSAP audits, supplier audits, or EU notified body audits. · ASQ Certified Software Quality Engineer, Certified Quality Engineer, Regulatory Affairs Certification, or similar professional certification. Location Remote (U.S.) temporarily, but able to transition to in-person work in New York City in approximately 6 months. Compensation Highly competitive salary + equity + benefits, commensurate with experience. If you’re excited about our mission, we want to hear from you. The base salary for this role is $200,000 - 270,000. How to Apply • If you’re excited to help shape the future of quantitative imaging biomarkers and medical AI, send your resume and a brief introduction to nathooi@sdi-global.ai (Isaac).

Machine Learning Engineer 4 (Python, AWS, SQL, GenAI) (Enterprise Platforms Technology)\n \n \n 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. \n \n Enterprise Platforms Technology (EPTech) comprises many of Capital One’s most important enterprise platforms. We play an essential role in establishing practices for building technology solutions across the company, while also delivering capabilities that exemplify those practices. \n \n Team: \n The Marketing and Messaging team is responsible for delivering hyper-personalized messages and experiences that will delight the customer, attract prospects and drive increasing business value. The team builds scalable platforms that deliver omnichannel messages in owned and paid Adtech channels. \n \n What You’ll Do: \n\n • 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:\n, • 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\n, • 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)\n, • Solve complex problems by writing and testing application code, developing and validating ML models, and automating tests and deployment \n, • 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\n, • Retrain, maintain, and monitor models in production\n, • Leverage or build cloud-based architectures, technologies, and/or platforms to deliver optimized ML models at scale\n, • Construct optimized data pipelines to feed ML models\n, • Leverage continuous integration and continuous deployment best practices, including test automation and monitoring, to ensure successful deployment of ML models and application code \n, • 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\n, • Use programming languages like Python, Scala, or Java\n\n \n Basic Qualifications: \n\n • Bachelor's Degree or higher in Computer Science, Machine Learning or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)\n, • At least 4 years of experience programming with Python, Java, Golang, or C++\n, • At least 4 years of Machine Learning experience using industry standard frameworks PyTorch or Tensorflow and libraries (Pandas, NumPy, Scikit-learn)\n, • At least 4 years of experience using and operating large scale distributed systems (Spark, Ray) to prepare AI/ML data\n, • At least 2 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\n\n \n Preferred Qualifications: \n\n • Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field\n, • 3+ years of experience optimizing ML algorithms, configurations, and infrastructure\n, • 3+ years of experience following software development best practices including source control, testing, code reviews, CI/CD, etc. \n, • 3+ 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.\n, • 3+ 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)\n, • 3+ years of experience designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models.\n, • 1+ years of experience as a technical lead developing ML solutions using industry best practices, patterns, and automation \n, • Authored/co-authored a paper on a ML technique, model, or proof of concept\n\n \n At this time, Capital One will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (e.g. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-3, and O-1, or any other forms of work authorization that require immigration support from an employer). \n \n \n 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. \n McLean, VA: $197,300 - $225,100 for Machine Learning Engineer 4\n \n New York, NY: $215,200 - $245,600 for Machine Learning Engineer 4\n \n Plano, TX: $179,400 - $204,700 for Machine Learning Engineer 4\n \n Richmond, VA: $179,400 - $204,700 for Machine Learning Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for Machine Learning Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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 AI Engineer (Remote Eligible)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Set the technical direction for enterprise-wide AI architecture - unifying tooling, observability, and deployment standards across teams\n, • Own the design and integration of model routing, caching, and orchestration systems that support hybrid and multi-model workloads\n, • Champion responsible AI principles across all system design, embedding transparency, reproducibility, and fairness-by-design\n, • Drive internal education, mentorship, and dissemination of best practices through architecture councils and AI guilds.\n\n \n Capital One is open to hiring a Remote Employee for this opportunity. \n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 8 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI and ML algorithms or technologies\n, • At least 8 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience designing AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 8+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience architecting, designing, developing, integrating, delivering, and supporting complex AI systems \n, • Demonstrated ability to lead and mentor multiple engineering teams and influence cross-functional stakeholders up to the VP level\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers\n, • Proven track record of defining and operationalizing enterprise AI architecture standards, including data pipeline governance, observability and evaluation frameworks\n, • Experience leading federated or multi-cloud AI strategies to maximize resilience, compliance and compute efficiency\n, • Demonstrated success influencing research-to-production promotion processes - guiding model handoff, evaluation and productization\n, • Experience defining north-star metrics for AI systems that balance business value, innovation velocity, cost, and ethical responsibility \n, • Experience right-sizing models, instance counts, and hardware types given requirements (e.g., context length, token inputs, token outputs)\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Remote (Regardless of Location): $244,700 - $279,200 for Staff AI Engineer\n \n Cambridge, MA: $269,100 - $307,200 for Staff AI Engineer\n \n McLean, VA: $269,100 - $307,200 for Staff AI Engineer\n \n New York, NY: $293,600 - $335,100 for Staff AI Engineer\n \n San Francisco, CA: $293,600 - $335,100 for Staff AI Engineer\n \n San Jose, CA: $293,600 - $335,100 for Staff AI Engineer\n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

AI Engineer 4 (AI Foundations: Benchmarking, Evaluation, and Explainability)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One.\n, • Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc.\n, • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.\n, • Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems.\n, • Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.\n, • Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment\n, • Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift\n, • Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines\n, • Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met\n, • Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation\n\n \n The Ideal Candidate: \n\n • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good\n, • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production\n, • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven\n, • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss\n, • You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown\n\n \n Basic Qualifications: \n\n • Bachelor's Degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies\n, • At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java\n\n \n Preferred Qualifications: \n\n • Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy\n, • 6+ years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud)\n, • Experience designing, developing, delivering, and supporting AI services\n, • Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang\n, • Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost\n, • Experience in building agentic AI systems and agentic workflows\n, • Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production\n, • Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale\n, • Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules\n, • Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms\n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Job Description The IB Tech & CRM/Analytics team is a highly strategic and cross-functional team responsible for leading the firm’s global digitalization effort. This initiative, spanning all client-facing business units and corporate functions, will drive innovation and strategic change through technology, data science, and deep analytics. The team partners with key business leaders and industry experts to build transformational technology to drive revenue, maximize efficiency, and optimize the allocation of resources. The IB Tech & CRM/Analytics team is at the forefront of Jefferies’ cloud initiative, leveraging best-in-class cloud-based technologies to replace legacy on-premises solutions to provide intelligent trend insights, actionable opportunities, decision support, and transparency into all client and business-related activities. Job Highlights: • Exciting and unique opportunity to be a member of our corporate IB Tech & CRM/Analytics Team, tackling our toughest and most exciting data engineering challenges across multiple divisions in Jefferies., • Modern, fully cloud-native, tech stack that leverages several AWS products to orchestrate an event driven data distribution platform., • Collaborate with our team of passionate and innovative data specialists, application developers and product managers. Key Responsibilities: We are looking for a Senior Java engineer who will: • Contribute to the end-to-end SDLC process on high-impact Madison projects, from conception for new –maintenance for existing, design, implementation, testing, release, and support., • Facilitate alignment across IB Tech & CRM/Analytics teams on goals, outcomes, priorities, deadlines, and deliverables., • Influence, mentor, and collaborate with a distributed set of engineers, within multiple time zones, to set clear standards and best practices, • Write readable, testable, and maintainable code, • Drive innovation of new technologies Experience Needed: • 8+ years of experience with Java development, • Excellent written and verbal communication skills with the ability to present complex technical solutions in a clear and concise manner, • Hands on experience designing, developing, and delivering Java-based APIs (GraphQL/OpenAPI/gRPC) and Microservices using Spring Boot and AWS products (ECR/EKS/EC2/Beanstalk), • Experience with Streaming Technologies like Kafka, including designing and developing complex, scalable, and high-performance applications. Proven track record of delivering robust and efficient solutions in a fast-paced environment., • Experience in working with SQL building Stored Procedures, Functions and Data Warehousing solutions., • Strong problem-solving skills and design skills with focus on distributed, highly available, and fault tolerant systems, • Experience in developing TDD/BDD unit-tests and work with Quality Assurance team members on defect triage and resolution., • Proactively participates in Agile Ceremonies like Sprint Planning, Backlog Grooming etc., and experience in working with virtual teams., • Provides Leadership skills in mentoring team members, resolving technical challenges and performing code reviews in a peer programming environment., • Experience building systems from scratch, demonstrating a deep understanding of software architecture and design principles., • In-depth knowledge of Kafka and its ecosystem, with prior experience in event-driven architecture. Ability to design and develop robust data pipelines and streaming applications., • Experience with AWS EKS (Elastic Kubernetes Service), including deploying and managing containerized applications. Strong understanding of CI/CD pipelines and containerization technologies such as Docker and Kubernetes., • Strong multi-tasking skills and able to learn new technologies quickly Good to Have: • Exposure to Front-End web development (Angular/React/JavaScript/Typescript), • Exposure to Financial Services & Investment Banking business domain., • Exposure to Salesforce or similar CRM Eco-System., • Exposure to Business Intelligence tools (Tableau CRM, Cognos, PowerBI, etc.)., • Exposure to ETL & Data Engineering tools like Mulesoft, StreamSets & Databricks. Primary Location Full Time Salary Range of $150,000 - $220,000.

AI Engineer 4 (AI Foundations: LLM Customization, Finetuning, Reinforcement Learning)\n \n \n At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. \n \n Team Description: \n The Intelligent Foundations and Experiences (IFX) team is at the center of bringing our vision for AI at Capital One to life. We work hand-in-hand with our partners across the company to advance the state of the art in science and AI engineering, and we build and deploy proprietary solutions that are central to our business and deliver value to millions of customers. Our AI models and platforms empower teams across Capital One to enhance their products with the transformative power of AI, in responsible and scalable ways for the highest leverage impact. \n \n What You’ll Do: \n\n • \n Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. \n • \n Design, develop, test, deploy, and support AI software components including foundation model training, large language model inference, agents and multi-agent workflows, similarity search, guardrails, model evaluation, experimentation, governance, and observability, etc. \n • \n Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more. \n • \n Invent and introduce state-of-the-art foundation model optimization techniques to improve the performance — scalability, cost, latency, throughput — of large scale production AI systems. \n • \n Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. \n • \n Own the end-to-end architecture for complex AI systems - ensuring maintainability, observability, and ethical alignment \n • \n Define and maintain service-level objectives (SLOs) for AI reliability, including latency, uptime, and model performance drift \n • \n Collaborate with infrastructure engineering to optimize GPU/TPU utilization and accelerate model inference pipelines \n • \n Lead cross-functional technical reviews for new AI system deployments, ensuring security, data governance, and compliance standards are met \n • \n Mentor Principal and Senior Associates on scalable design, performance tuning and research-to-production translation \n\n \n The Ideal Candidate: \n\n • \n You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good \n • \n Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production \n • \n You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven \n • \n You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss \n • \n You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown \n\n \n Basic Qualifications: \n\n • \n Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 4 years of experience developing AI and ML algorithms or technologies, or a Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 2 years of experience developing AI and ML algorithms or technologies \n • \n At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java \n\n \n Preferred Qualifications: \n\n • \n Experience leading development AI systems with tradeoff decisions around cost, latency, throughput and accuracy \n • \n 6 years of experience deploying scalable and responsible AI solutions on cloud platforms (e.g. AWS, Google Cloud, Azure, or equivalent private cloud) \n • \n Experience designing, developing, delivering, and supporting AI services \n • \n Experience developing AI and ML algorithms or technologies (e.g. LLM Inference, Similarity Search and VectorDBs, Guardrails, Memory) using Python, C++, C#, Java, CUDA, or Golang \n • \n Experience developing and applying state-of-the-art techniques for optimizing training and inference software to improve hardware utilization, latency, throughput, and cost \n • \n Experience in building agentic AI systems and agentic workflows \n • \n Passion for staying abreast of the latest AI research and AI systems, and judiciously apply novel techniques in production \n • \n Proficiency in designing distributed systems for model training, evaluation, and online inference at petabyte scale \n • \n Experience defining AI model governance processes, including producibility, lineage tracking, and automated retaining schedules \n • \n Demonstrated ability to influence architectural decisions across multiple AI product lines or platforms \n\n \n Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. \n \n 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. \n Cambridge, MA: $197,300 - $225,100 for AI Engineer 4\n \n McLean, VA: $197,300 - $225,100 for AI Engineer 4\n \n New York, NY: $215,200 - $245,600 for AI Engineer 4\n \n San Francisco, CA: $215,200 - $245,600 for AI Engineer 4\n \n San Jose, CA: $215,200 - $245,600 for AI Engineer 4\n \n \n \n \n \n \n \n \n \n \n \n \n \n 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. \n 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.\n \n 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. \n This role is expected to accept applications for a minimum of 5 business days.\n \n 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.\n \n \n 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. \n \n For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com \n \n 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. \n \n 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).

We are working with a global investment firm that combines technology, quantitative research and investment expertise across global financial markets. They are looking for an End User Experience Engineer to join their engineering team, focused on building and operating modern endpoint platforms across a global user base. This is an engineering-focused EUC role, centred around standardisation, automation and reliability rather than traditional desktop support. You’ll work across Apple platforms, mobile devices, secure remote access and wider end-user technologies, partnering closely with identity, networking, security and application teams. Key Responsibilities: • Engineer and manage secure remote access solutions, including SASE/ZTNA, • Own core engineering for Apple endpoints and mobility, including: Jamf pro admin, Apple business manager, iOS/macOS lifecycle management, • Provide support across Android Enterprise, • Troubleshoot issues across endpoints, identity, networking and SaaS applications, • Support application packaging, deployment and lifecycle management, • Build automation and reporting using Python, Bash/Zsh and APIs, • Create and maintain runbooks, operational documentation and change validation procedures, • Leverage AI/LLM tools to improve troubleshooting, automation and operational efficiency Key Requirements: • 5+ years of experience in EUC, Endpoint Engineering or End User Platform Engineering, • Strong hands-on experience with Apple platforms and macOS, • Experience managing secure remote access solutions at scale, • Experience managing iOS/iPadOS devices, including enrollment, compliance and application deployment, • Working knowledge of Android Enterprise, • Strong scripting and automation skills using Python, Bash or Zsh, • Comfortable working with APIs, • Strong troubleshooting skills across endpoints, identity and network dependencies, • Enterprise experience, ideally within financial services Desirable Requirements: • Experience with Intune/SCCM and the Windows endpoint ecosystem, • Experience supporting VDI/Citrix environments, • Experience with application packaging and deployment, • Practical experience using AI/LLM tools to improve operational efficiency, • Experience supporting a global user base, • Strong communication and cross-team collaboration skills

Hi, Title: Windows Site Reliability Engineer (SRE) Location: Jersey City, NJ Ideal Candidate: A strong candidate should have a combination of Windows administration + application packaging + SCCM/Intune + PowerShell + CI/CD + production support experience, along with the ability to work directly with software vendors. Job Summary: We are looking for a Windows Site Reliability Engineer to support, deploy, monitor, and maintain third-party business applications in a Windows environment. The engineer will work closely with vendors, application teams, and infrastructure teams to ensure applications are reliable, secure, and available. Key Responsibilities • Support and manage Windows-based third-party applications including thin-client, thick-client, and web applications., • Work with vendors on software releases, patches, defects, and technical issues., • Package and deploy Windows applications using MSI, MST, MSIX, App-V, and PSADT., • Manage application deployments through SCCM/MECM and/or Intune., • Build and maintain CI/CD pipelines using Azure DevOps, Jenkins, or GitHub Actions., • Deploy applications across Dev, Test, UAT, and Production environments., • Support web applications hosted on IIS and applications running on Citrix, RDS, or AVD., • Create and maintain monitoring, alerts, dashboards, and application health checks., • Troubleshoot production issues and participate in incident management and root-cause analysis (RCA)., • Automate repetitive tasks using PowerShell to reduce manual work., • Manage application upgrades, patches, versions, and end-of-life software., • Create runbooks, documentation, and knowledge articles., • Support application databases and troubleshoot connectivity issues using SQL Server., • Follow formal change management/ITIL processes for production deployments. Required Skills • 5+ years of experience in Windows application support, SRE, systems engineering, or application operations., • Strong Windows Server and Windows Client administration., • Hands-on experience with application packaging: MSI/MST, MSIX, App-V, PSADT., • Experience with SCCM/MECM and/or Intune., • Strong PowerShell scripting and automation skills., • Experience with IIS, Citrix, RDS, or AVD., • Experience supporting third-party/vendor applications., • CI/CD experience with Azure DevOps, Jenkins, or GitHub Actions., • Experience with Git and source control., • Knowledge of Active Directory, Group Policy, Windows Registry, services, and permissions., • Experience with monitoring/observability tools such as Splunk, Dynatrace, Datadog, SCOM, or Azure Monitor., • Working knowledge of SQL Server., • Experience with production deployments, change management, and troubleshooting., • Strong communication and documentation skills. Preferred Skills • Terraform, Ansible, or PowerShell DSC., • Azure or AWS experience with Windows workloads., • Windows/.NET application containerization or MSIX App Attach., • Vulnerability remediation and patch management., • Knowledge of SRE practices, error budgets, toil reduction, and capacity planning., • Microsoft Azure, Citrix, or ITIL certifications.

Analytics Engineer New York, NY · Data & Engineering · Full-Time · Hybrid About the Company Our client is a fast-growing, venture-backed music company that helps independent music creators monetize and grow their careers. The company partners with creators to unlock the value of their catalogs through flexible, straightforward deals, and also offers catalog management, distribution, and marketing services. It has partnered with a large and growing roster of independent creators around the world, helping them monetize their music on their own terms and reach new audiences. Backed by leading investors and significant capital raised to fund independent creators, the company is driven by a belief in independence and financial empowerment and is building a more sustainable future for music creators everywhere. The company has offices in several major cities, including New York, and offers a competitive benefits package that includes healthcare coverage, flexible paid time off, and a hybrid work model. It is an ambitious, high-ownership environment where your work will have an immediate, tangible impact. Role Overview We’re looking for an Analytics Engineer to join as an early member of the Data Team and help build the systems that power artist sourcing, track pricing, portfolio management, and catalog growth. This role sits at the intersection of analytics, engineering, and product with high autonomy, technical ownership, and direct business impact. You will report to the Head of Data & Analytics and help define the future of the company’s data products. Because data fuels everything the company does, the Data Team works horizontally across the entire organization. While your core focus will be deal-flow optimization and catalog pricing, which sit at the core of the business model, you’ll also collaborate with music-industry veterans, financial experts, and senior engineers and data scientists across a variety of initiatives. You Will: • Own the core models, transformations, and analytics products that drive track and catalog pricing decisions • Partner with Finance & Management to uncover insights into catalog performance, revenue drivers, and portfolio health • Collaborate with Data Science to refine predictive models and integrate third-party and proprietary datasets • Work closely with Product to design internal tools, workflows, and decision support systems • Identify and resolve data quality and pipeline issues, ensuring a reliable analytics foundation across teams • Dive deep into streaming performance and catalog behavior to uncover optimization opportunities for acquired catalogs • Explore and build LLM-powered internal tools that automate data workflows Requirements: • 5+ years in analytics engineering or data analytics roles within high-growth environments • Strong SQL & Python skills for data modeling, transformation, and automation, • Hands-on experience with BI tools (Looker, Tableau, or equivalent), • Ability to translate complex data into clear, actionable insights for technical and non- technical stakeholders • A builder mindset: autonomous, curious, proactive, and excited to shape a fast-moving analytics stack • Experience with music streaming data, KPIs, or creator-economy platforms (preferred but not required) • Experience collaborating on or implementing LLM-powered internal tools or workflows (preferred but not required) Compensation $100,000 to $140,000 a year

Business Description: Our client is the technology organization at the core of businesses and growth initiatives. We design and deliver enterprise platforms and services that manage risk, create efficiency, and improve transparency across the firm and its global community of investors and portfolio companies. It operates with an entrepreneurial mindset, collaborative, fast-moving, and outcome-driven, while maintaining the rigor required to support a complex global enterprise. We value leadership, accountability, and continuous improvement, and we expect our team members to help the firm maintain its competitive edge. Job Description: The client is seeking a Unified Communications Engineer to join our Enterprise Technology UC team. This role will be responsible for supporting and enhancing the firm's Unified Communications and collaboration platforms, with a primary focus on Zoom. The ideal candidate has experience working in a fast-paced enterprise environment supporting voice, video, and collaboration technologies. They will partner closely with Operations and Service Desk teams to support escalations, as well as business stakeholders to deliver reliable communication services and exceptional user experiences. In addition, this individual will assist with platform administration, governance, and policy management. This position requires an engineer with hands-on UC administration experience who is looking to broaden their expertise across enterprise collaboration, conferencing, voice, and platform management. Key Responsibilities: • Administer and support Zoom services including Zoom Meetings, Zoom Phone, user provisioning, and group management., • Support and troubleshoot escalations for voice, video, and collaboration technologies across the enterprise., • Support enterprise UC devices, desk phones, room devices, and collaboration peripherals., • Provide occasional onsite and field support for deployments, conference rooms, and executive users when necessary., • Develop and maintain knowledge base articles, operational documentation, support runbooks, and user guides to support the Operations and Service Desk teams., • Gain familiarity with adjacent technologies including trading communications platforms (Cloud9), dictation solutions, and compliance-related communication technologies., • Participate in platform upgrades, change control process, testing, and continuous improvement initiatives. Required Qualifications: • 5+ years of experience supporting Unified Communications, collaboration, or workplace technology platforms., • Strong hands-on experience administering and supporting Zoom in an enterprise environment., • Experience supporting enterprise voice, video conferencing, and collaboration solutions., • Familiarity with the Zoom Workplace ecosystem at minimum Zoom Phone, Zoom Meetings, and Zoom Rooms., • Experience supporting conference room and AV technologies., • Strong troubleshooting and problem-solving skills., • Excellent verbal and written communication skills., • Experience creating technical documentation, knowledge base articles, and support procedures., • Ability to work effectively in a fast-paced, customer-focused environment., • Willingness to provide onsite and field support when required. Preferred Qualifications: • Financial services industry experience., • Experience with Microsoft Teams and Teams Meetings, • Exposure to Cloud9, trading communications platforms, or compliance recording solutions., • Experience supporting dictation platforms., • Familiarity with ServiceNow or other ITSM platforms., • Basic understanding of VoIP, SIP, and UC infrastructure.