Capital One
AI Engineer 4
$197K–$246K
New York, NY +3 · Full-time · Posted Sep 18, 2026
- Location
- New York, NY
McLean, VA
Cambridge, MA
San Jose, CA - Experience
- At least 4 years developing AI and ML algorithms or technologies with a Bachelor’s degree, or at least 2 years with a Master’s degree; at least 4 years programming. Preferred: 6 years deploying scalable and 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 operate foundational AI systems and AI-powered products, optimizing large-scale model performance, reliability, and responsible deployment.
What you'll do
- Design, develop, deploy, and support AI components such as foundation-model training, LLM inference, agent workflows, similarity search, guardrails, evaluation, and observability.
- Optimize production AI systems for scalability, cost, latency, throughput, and hardware utilization; define reliability objectives and own system architecture.
- Partner with cross-functional teams to set technical direction, review deployments for security and governance, and mentor engineers.
What they ask for
- Bachelor’s degree in a listed or related field plus at least 4 years developing AI/ML algorithms or technologies, or a Master’s degree in a listed or related field plus at least 2 years of that experience.
- At least 4 years programming with Python, Go, Scala, CUDA, or Java.
Nice to have
- Experience leading AI system development with cost, latency, throughput, and accuracy tradeoffs.
- Experience deploying scalable, responsible AI solutions on cloud platforms; 6 years specified.
Pay
$197,300 - $225,100 USD base salary (Cambridge, MA); $197,300 - $225,100 USD base salary (McLean, VA); $215,200 - $245,600 USD base salary (New York, NY); $215,200 - $245,600 USD base salary (San Jose, CA)
Tools
AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, Python, Go, Scala, CUDA
AI focus
Develop foundational and applied AI systems, including foundation-model training, LLM inference, agentic workflows, model optimization, evaluation, guardrails, governance, and observability.
Model-written summary · the original posting is authoritative