Job description

Director AI Engineering (Remote Eligible) At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent — along with our deep experience in machine learning — position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build. Team Description: The 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. What You’ll Do: Partner with a cross-functional team of engineers, research scientists, technical program managers, and product managers to deliver AI-powered products that change how our associates work and how our customers interact with Capital One. Oversee the design, development, testing, deployment, and 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. 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. Invent and introduce state-of-the-art techniques to improve the scalability, cost, throughput, and reliability of large-scale distributed training and fine-tuning. Own GPU capacity planning and cost governance: right-size clusters, instance types, and quotas to the needs of training and experimentation workloads across teams. Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One. Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI. Translate the enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline Scale AI engineering practices across teams through shared infrastructure, reusable components, and unified observability and governance frameworks Establish enterprise standard for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards The Ideal Candidate: You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production You get fulfillment from empowering others to achieve their potential and you actively drive professional development through mentoring and coaching. You are hands-on when necessary and lead by example You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enables you to see and exploit optimization opportunities that others miss You are a resilient trailblazer who can forge new paths to achieve business goals when the route is unknown Capital One is open to hiring a Remote Employee for this opportunity. Basic Qualifications: 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 At least 3 years of people leadership experience Preferred Qualifications: 5 years of experience managing and leading an engineering team 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) 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 Experience with the ML orchestration and scheduling stack (e.g., Kubernetes, Kubeflow, Kueue, Slurm, Ray, KServe, vLLM) Experience operating large GPU fleets with a focus on reliability, fault tolerance, utilization, and cost efficiency Experience right-sizing GPU clusters, instance types, interconnect, and quotas to training and experimentation workload requirements (e.g., model size, parallelism strategy, throughput targets) Passion for staying abreast of the latest AI and ML-systems research, and judiciously applying novel training and optimization techniques Excellent communication and presentation skills, with the ability to articulate complex AI and infrastructure concepts to peers Experience building and leading a multi-team AI organization delivering multiple enterprise capabilities concurrently Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews) Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineer Cambridge, MA: $269,100 - $307,200 for Director, AI Engineer McLean, VA: $269,100 - $307,200 for Director, AI Engineer New York, NY: $293,600 - $335,100 for Director, AI Engineer San Francisco, CA: $293,600 - $335,100 for Director, AI Engineer San Jose, CA: $293,600 - $335,100 for Director, AI Engineer Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter. This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan. Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website . Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries. If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation capitalone.com . All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations. For technical support or questions about Capital One s recruiting process, please send an email to Careers capitalone.com Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

Requirements

Must-haves

Director AI Engineering (Remote Eligible)
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.
Invent and introduce state-of-the-art techniques to improve the scalability, cost, throughput, and reliability of large-scale distributed training and fine-tuning.
Own GPU capacity planning and cost governance: right-size clusters, instance types, and quotas to the needs of training and experimentation workloads across teams.
Contribute to the technical vision and the long term roadmap of foundational AI systems at Capital One.
Attract and retain top talent in the AI industry and nurture personal and professional development for your team. Foster a culture of learning and staying abreast of the state-of-the-art in AI.
Translate the enterprise AI strategy into portfolio-level execution plans across multiple product areas, balancing innovation with delivery discipline
Scale AI engineering practices across teams through shared infrastructure, reusable components, and unified observability and governance frameworks
Establish enterprise standard for Responsible AI, including fairness metrics, model evaluation protocols, documentation requirements, and audit readiness
Partner with research, compliance, and enterprise risk teams to ensure deployed systems meet emerging ethical and regulatory standards
You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good
Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production

Nice-to-haves

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
Experience with the ML orchestration and scheduling stack (e.g., Kubernetes, Kubeflow, Kueue, Slurm, Ray, KServe, vLLM)
Experience operating large GPU fleets with a focus on reliability, fault tolerance, utilization, and cost efficiency
Experience right-sizing GPU clusters, instance types, interconnect, and quotas to training and experimentation workload requirements (e.g., model size, parallelism strategy, throughput targets)
Passion for staying abreast of the latest AI and ML-systems research, and judiciously applying novel training and optimization techniques
Excellent communication and presentation skills, with the ability to articulate complex AI and infrastructure concepts to peers
Experience building and leading a multi-team AI organization delivering multiple enterprise capabilities concurrently
Proven ability to expand and execute long-term AI platform strategies aligned to enterprise priorities and regulatory frameworks
Experience establishing cross-functional operating rhythms and review cadences (OKRs, AI governance councils, quarterly reviews)
Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Remote (Regardless of Location): $244,700 - $279,200 for Director, AI Engineer
Cambridge, MA: $269,100 - $307,200 for Director, AI Engineer

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Keywords to mirror

aimachine learningmlrestawsazurepythongokubernetes

Platform: workday
Effort: long

Benefits

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Vision

Professional Development