Senior AI Engineer - Scalable ML Platforms

Capital One; San Francisco (CA); On-site; USD 251,000 - 286,000; Full time

Job summary

Capital One is seeking an AI Engineer 5 in San Francisco to help design, implement, and optimize AI systems across complex workflows. You will work with engineers, researchers, and product managers to deliver scalable AI-powered solutions that enhance both employee and customer experiences.

The role requires strong Python and ML skills, hands-on experience with large models, and the ability to balance performance with cost in production environments.

Qualifications

• Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields plus at least 6 years of experience developing AI/ML algorithms or technologies.
• At least 6 years of experience programming with Python, Go, Scala, CUDA, or Java.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products that change how associates work and how customers interact with Capital One.
• Design, develop, test, deploy, and support AI software components including foundation model training, LLM inference, agents, and multi-agent workflows.
• Leverage Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch, and more.
• Invent and introduce foundation model optimization techniques to improve performance, cost, latency, throughput.

Skills

Python

Cross-functional collaboration

Machine learning

Communication skills

Problem solving

Education

Bachelor's degree in CS/AI/Engineering with 6+ years

Master's degree in CS/AI/Engineering with 4+ years

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Open Source tools

Job description

Capital One is seeking an AI Engineer 5 in San Francisco to help design, implement, and optimize AI systems across complex workflows. You will work with engineers, researchers, and product managers to deliver scalable AI-powered solutions that enhance both employee and customer experiences.

The role requires strong Python and ML skills, hands-on experience with large models, and the ability to balance performance with cost in production environments.