Capital One
AI Engineer 5 (AI Foundations, VLM Customization)
$230K–$286K
San Jose, CA +3 · Full-time · Posted Sep 18, 2026
- Location
- San Jose, CA
McLean, VA
Cambridge, MA
New York, NY - Experience
- At least 6 years developing AI/ML algorithms or technologies with a relevant bachelor’s degree, or at least 4 years with a relevant master’s degree; at least 6 years programming. 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 for this position.
About the job
Build and optimize scalable foundation-model and multimodal AI systems and products, including model orchestration, inference, and agent workflows.
What you'll do
- Design, develop, deploy, and support AI components such as foundation-model training, LLM inference, agents, similarity search, guardrails, evaluation, and observability.
- Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization; lead cost-performance reviews.
- Shape technical roadmaps and standards, lead design 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; alternatively, a relevant master’s degree plus at least 4 years.
- At least 6 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading scalable AI system development and making cost, latency, throughput, and accuracy tradeoffs.
- Experience deploying responsible AI on cloud platforms and optimizing training or inference systems.
Pay
USD $229,900 - $262,400 base salary (Cambridge, MA and McLean, VA); USD $250,800 - $286,200 base salary (New York, NY and San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Foundation-model and VLM customization, LLM inference, agentic workflows, multimodel orchestration, similarity search, guardrails, evaluation, and optimization of production AI systems.
Model-written summary · the original posting is authoritative