Senior AI Engineer: Foundation Models & Production ML

Capital One; New York (NY); On-site; USD 215,000 - 246,000; Full time

Job summary

Capital One is seeking an AI Engineer 4 (MLX) to design, develop, and deploy AI-powered systems at scale. You will collaborate with engineers, scientists, PMs and product partners to advance AI capabilities, including foundation model training, LLM inference, agents and multi-agent workflows, and governance.

Strong Python/Java/CUDA skills and cloud experience are essential. You will contribute to the technical vision, own end-to-end architectures, optimize performance and cost, and ensure

Qualifications

• Bachelor's degree in CS/AI/EE/CE or related fields with 4+ years of AI/ML algo development or Master's with 2+ years
• 4+ years of Python/Go/Scala/CUDA/Java programming experience

Responsibilities

• Partner with cross-functional team to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components
• Leverage Open Source and SaaS AI technologies (AWS Ultraclusters, Huggingface, VectorDBs, PyTorch)
• Invent model optimization techniques to improve performance, latency and cost
• Own end-to-end architecture for complex AI systems and ensure observability and ethics
• Define and maintain SLOs for AI reliability
• Collaborate with infrastructure to optimize GPU/TPU utilization
• Lead technical reviews for AI system deployments
• Mentor senior engineers on scalable design and production translation

Skills

Python

Go

Scala

CUDA

Java

Education

Bachelor's degree in CS/AI/EE/CE or related fields

Master's degree in CS/AI/EE/CE or related fields

Tools

AWS Ultraclusters

Huggingface

VectorDBs

PyTorch

Job description

Capital One is seeking an AI Engineer 4 (MLX) to design, develop, and deploy AI-powered systems at scale. You will collaborate with engineers, scientists, PMs and product partners to advance AI capabilities, including foundation model training, LLM inference, agents and multi-agent workflows, and governance.

Strong Python/Java/CUDA skills and cloud experience are essential. You will contribute to the technical vision, own end-to-end architectures, optimize performance and cost, and ensure