Senior AI Engineer - Remote, Scalable ML Systems

Capital One; Nashville (TN); Remote; USD 244,700 - 279,200; Full time

Job summary

Capital One is seeking a Distinguished AI Engineer to build responsible and reliable AI systems and real-time, personalized experiences. You will work with a cross-functional team of engineers, scientists, and product managers to design and deploy AI software components, including foundation models and LLM inference, using a broad stack of tools.

The role emphasizes optimization techniques, governance, observability, and scalable AI infrastructure.

Qualifications

• 8+ years AI/ML algorithm development experience or higher education with equivalents.
• Experience with Python, Go, Scala, or Java for production AI systems.
• Experience deploying scalable AI on cloud platforms and designing complex AI systems.
• Ability to lead and mentor multiple engineering teams and influence stakeholders.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products.
• Design, develop, test, deploy, and support AI software components (LLM inference, training, governance).
• Leverage Open Source and SaaS AI technologies (AWS Ultraclusters, Huggingface, VectorDBs, PyTorch).
• Invent state-of-the-art LLM optimization techniques to improve performance, cost, latency, and throughput.
• Contribute to the technical vision and long-term roadmap of foundational AI systems.

Skills

Python

Go

Scala

Java

AI/ML algorithms

Cross-functional collaboration

System design

Education

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

Master's degree in Computer Science, Computer Engineering, or relevant field

Tools

AWS Ultraclusters

Huggingface

VectorDBs

Nemo Guardrails

PyTorch

Job description

Capital One is seeking a Distinguished AI Engineer to build responsible and reliable AI systems and real-time, personalized experiences. You will work with a cross-functional team of engineers, scientists, and product managers to design and deploy AI software components, including foundation models and LLM inference, using a broad stack of tools.

The role emphasizes optimization techniques, governance, observability, and scalable AI infrastructure.