Senior AI Engineer – Scalable Foundation Models

Capital One; McLean (VA); On-site; USD 197,000 - 225,000; Full time

Benefits offered by this job

Performance-based incentives

Health benefits

Job summary

Capital One is seeking an experienced AI Engineer 4 to design, develop, and deploy AI-powered products that transform how associates and customers interact with Capital One. You will work across engineering, research, and product teams to advance AI capabilities and ensure responsible, scalable systems.

The role involves building and evaluating foundation models, optimizing inference pipelines, and contributing to the long-term AI strategy with governance and observability in mind.

Qualifications

• Bachelor's degree in CS/AI or related field with 4+ years in AI/ML.
• Master's degree with 2+ years in AI/ML.
• At least 4 years of experience programming with Python, Go, Scala, CUDA, or Java.

Responsibilities

• Partner with cross-functional team to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including foundation models and inference.
• Leverage Open Source and SaaS AI tech such as AWS Ultraclusters, Huggingface, VectorDBs, PyTorch.
• Invent and optimize foundation model techniques for performance, cost, latency, and throughput.
• Define and maintain the architectural vision and roadmap for AI systems.

Skills

Python

Go

Scala

CUDA

Java

Distributed systems

ML algorithms

Cloud platforms

Model training

Guardrails

Education

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering, or related fields

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

Capital One is seeking an experienced AI Engineer 4 to design, develop, and deploy AI-powered products that transform how associates and customers interact with Capital One. You will work across engineering, research, and product teams to advance AI capabilities and ensure responsible, scalable systems.

The role involves building and evaluating foundation models, optimizing inference pipelines, and contributing to the long-term AI strategy with governance and observability in mind.