Senior AI Foundations Engineer - Scalable LLM & AI Infra

Capital One; Cambridge (MA); On-site; USD 162,000 - 185,000; Full time

Job summary

Capital One is seeking a Senior AI Engineer to design, deploy, and optimize AI systems that power real-time customer experiences. You will work with engineers, researchers, and product managers to deliver scalable AI components and guardrails, using PyTorch, Hugging Face, and vector databases in production.

You will also contribute to the technical roadmap and continually improve training/inference efficiency while ensuring responsible AI practices across platforms and products.

Qualifications

• Bachelor's or Master's in CS/AI/EE/CE or related field with required experience.
• Proven experience developing AI/ML algorithms or technologies.
• Strong proficiency in Python, Go, Scala, or Java.

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 tech stacks like AWS, Hugging Face, and PyTorch.
• Develop state-of-the-art LLM optimization techniques for production systems.
• Contribute to the technical vision and long-term roadmap for AI at Capital One.

Skills

Python

Go

Scala

Java

LLM inference

Similarity search

VectorDBs

Guardrails

Memory

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

Hugging Face

PyTorch

VectorDBs

Job description

Capital One is seeking a Senior AI Engineer to design, deploy, and optimize AI systems that power real-time customer experiences. You will work with engineers, researchers, and product managers to deliver scalable AI components and guardrails, using PyTorch, Hugging Face, and vector databases in production.

You will also contribute to the technical roadmap and continually improve training/inference efficiency while ensuring responsible AI practices across platforms and products.