Senior AI Platform Engineer - Inference & Optimization

Capital One; New York (NY); On-site; USD 251,000 - 286,000; Full time

Benefits offered by this job

Performance-based incentives

Competitive benefits package

Job summary

Capital One is hiring a Sr. Lead AI Engineer to drive AI systems across foundation models, inference optimization, and hosting platforms. You will work with a cross-functional team to build scalable AI software components and push state-of-the-art techniques in production.

The role emphasizes responsible AI, high-performance infrastructure, and collaboration across engineers, researchers, and product managers in a fast-paced setting.

Qualifications

• Bachelor's degree in Computer Science or related field with 6+ years of AI/ML experience, or a Master’s with 4+ years.
• 6+ years of programming in Python, Go, Scala, or Java.
• 7 years of experience deploying AI on cloud platforms (AWS, GCP, Azure).
• Experience leading and mentoring an engineering team.
• Experience with LLM inference, VectorDBs, guardrails, and memory techniques.
• Strong communication and problem-solving skills.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components including LLM inference and guardrails.
• Leverage Open Source and SaaS AI technologies to optimize performance, cost, and latency.
• Invent state-of-the-art optimization techniques for large-scale AI systems.
• Contribute to the long-term technical vision and roadmap for foundational AI systems.

Skills

Python

Go

Scala

Java

Mathematics

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

AWS Ultraclusters

Huggingface

VectorDBs

Nemo Guardrails

PyTorch

Job description

Capital One is hiring a Sr. Lead AI Engineer to drive AI systems across foundation models, inference optimization, and hosting platforms. You will work with a cross-functional team to build scalable AI software components and push state-of-the-art techniques in production.

The role emphasizes responsible AI, high-performance infrastructure, and collaboration across engineers, researchers, and product managers in a fast-paced setting.