Capital One
AI Engineer 5
$230K–$286K
San Jose, CA +2 · Full-time · Posted Oct 14, 2026
- Location
- San Jose, CA
New York, NY
Cambridge, MA - Experience
- At least 6 years developing AI/ML algorithms or technologies with a bachelor’s degree, or at least 4 years with a master’s degree; at least 6 years programming with a listed language. Preferred: 7+ years deploying scalable, responsible AI solutions on cloud platforms.
- Education
- Bachelor’s or master’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields.
- Visa sponsorship
- Capital One will consider sponsoring a new qualified applicant for employment authorization.
About the job
Build and optimize responsible, scalable AI systems and products, including foundation models, LLM inference, agents, and orchestration pipelines for Capital One.
What you'll do
- Design, develop, deploy, and support AI components and production systems, including model inference, agents, similarity search, evaluation, governance, and observability.
- Optimize foundation-model training and inference for scalability, cost, latency, throughput, and hardware utilization.
- Contribute to AI system roadmaps, lead design and cost-performance reviews, and mentor AI engineers.
What they ask for
- Bachelor’s degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or a related field plus at least 6 years developing AI/ML algorithms or technologies; or a master’s degree in one of these fields plus at least 4 years of that experience.
- At least 6 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading AI system development and making cost, latency, throughput, and accuracy tradeoffs.
- Experience deploying scalable, responsible AI on cloud platforms; developing agentic systems; optimizing training and inference; or integrating heterogeneous AI systems.
Pay
$229,900 - $262,400 USD base salary (Cambridge, MA); $250,800 - $286,200 USD base salary (New York, NY); $250,800 - $286,200 USD base salary (San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop and optimize foundation models, LLM inference, agents and multi-agent workflows, similarity search, AI orchestration, evaluation, guardrails, governance, and observability.
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