Lead AI Engineer: Foundations & LLM Tuning

Capital One; McLean (VA); On-site; USD 197,000 - 246,000; Full time

Job summary

Capital One seeks an experienced Lead AI Engineer to help build responsible AI foundations and scalable LLM customization capabilities. You will collaborate with engineers, researchers, and product managers to deliver AI-powered features across banking applications.

You will advance foundation model training, inference, guardrails, and observability with a broad stack including PyTorch, Huggingface, and VectorDBs, while optimizing performance, latency, and cost in production.

Qualifications

• Bachelor’s or Master’s degree in a relevant field with required experience in AI/ML.
• 4+ years programming in Python, Go, Scala or Java.
• Experience deploying scalable AI/ML solutions on cloud platforms.
• Experience designing AI services and optimizing training/inference.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components.
• Leverage Open Source and SaaS AI technologies across a broad stack.
• Invent state-of-the-art LLM optimization techniques for scale and cost.
• Contribute to the long-term technical vision and roadmap.

Skills

Python

Go

Scala

Java

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

Google Cloud

Azure

Huggingface

VectorDBs

Nemo Guardrails

PyTorch

Job description

Capital One seeks an experienced Lead AI Engineer to help build responsible AI foundations and scalable LLM customization capabilities. You will collaborate with engineers, researchers, and product managers to deliver AI-powered features across banking applications.

You will advance foundation model training, inference, guardrails, and observability with a broad stack including PyTorch, Huggingface, and VectorDBs, while optimizing performance, latency, and cost in production.