Senior AI Engineer, AI Foundations & LLM Systems

COMFORT SYSTEMS; San Jose (CA); On-site; USD 177,000 - 201,000; Full time

Job summary

Capital One, a leader in responsible AI, is seeking a Senior AI Engineer (AI Foundations) to advance our AI systems and foundation model capabilities. You will work with cross-functional teams to build, deploy, and optimize AI-powered products that impact millions of customers and associates.

You will contribute to training, inference, guardrails, and observability using a broad stack including PyTorch, VectorDBs, and cloud platforms, shaping the next generation of scalable AI infrastructure for

Qualifications

• Bachelor's or Master's degree as stated with required years of experience in AI/ML
• 3+ years programming in Python/Go/Scala/Java
• 4+ years deploying scalable AI solutions on cloud platforms
• Experience with AI/ML algorithms and technologies (LLM Inference, Similarity Search, VectorDBs)

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products
• Design, develop, test, deploy, and support AI software components (foundation models, LLM inference)
• Leverage Open Source and SaaS AI tech (AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch)
• Invent and optimize LLM techniques for performance, cost, latency
• Contribute to technical vision and long-term AI system roadmaps

Skills

Python

Go

Scala

Java

AWS

Google Cloud

Azure

Education

Bachelor's degree in Computer Science, AI, Electrical Engineering, Computer Engineering

Master's degree in Computer Science, AI, Electrical Engineering, Computer Engineering

Tools

AWS

Google Cloud

Azure

Job description

Capital One, a leader in responsible AI, is seeking a Senior AI Engineer (AI Foundations) to advance our AI systems and foundation model capabilities. You will work with cross-functional teams to build, deploy, and optimize AI-powered products that impact millions of customers and associates.

You will contribute to training, inference, guardrails, and observability using a broad stack including PyTorch, VectorDBs, and cloud platforms, shaping the next generation of scalable AI infrastructure for