Capital One
AI Engineer 4
$197K–$246K
Cambridge, MA +3 · Full-time · Posted Sep 29, 2026
- Location
- Cambridge, MA
McLean, VA
San Jose, CA
New York, NY - 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 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 scalable, responsible AI systems and products, including foundation models, LLM inference, agents, and supporting infrastructure.
What you'll do
- Design, develop, test, deploy, and support AI components and production systems.
- Optimize foundation model training and inference for scalability, cost, latency, throughput, and hardware utilization.
- Own AI system architecture and reliability; contribute to technical roadmaps and lead deployment reviews.
What they ask for
- Bachelor’s degree in a related field plus at least 4 years developing AI/ML algorithms or technologies, or a master’s degree in a 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 and making tradeoffs among cost, latency, throughput, and accuracy.
- 6+ years deploying scalable and responsible AI solutions on cloud platforms.
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 and optimize foundation models, LLM inference, agentic and multi-agent workflows, similarity search, guardrails, model evaluation, governance, and observability for responsible production AI.
Model-written summary · the original posting is authoritative