Director, AI Platform & Large‑Scale ML (Remote)

Capital One; Lincoln (NE); Remote; USD 245,000 - 279,000; Full time

Job summary

Capital One is seeking a Director of AI Engineering to lead the Generative AI Training platform and related infrastructure. This remote-eligible role involves overseeing distributed training, fine-tuning, and governance across teams while shaping long-term AI strategy and talent development.

You will partner with researchers, engineers, PMs, and compliance to deliver scalable, cost-efficient AI capabilities and enterprise-grade reliability.

Qualifications

• Bachelor or higher degree in CS/AI/related fields with strong AI/ML experience.
• 3+ years of people leadership experience.
• 5+ years managing and leading an engineering team.
• Experience building and operating large-scale ML/GPU training infrastructure.

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products for associates and customers.
• Oversee design, development, testing, deployment, and operation of core platforms.
• Make build-versus-buy decisions across Open Source and SaaS AI technologies.
• Invent techniques to improve scalability, cost, throughput, and reliability of distributed training.

Skills

Distributed training at scale

PyTorch

Kubernetes

Python

Go

C++

CUDA

DeepSpeed

Huggingface

ML systems

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

KServe

vLLM

Kubernetes

Kubeflow

Slurm

Ray

AWS

Huggingface

VectorDBs

Ultraclusters

Job description

Capital One is seeking a Director of AI Engineering to lead the Generative AI Training platform and related infrastructure. This remote-eligible role involves overseeing distributed training, fine-tuning, and governance across teams while shaping long-term AI strategy and talent development.

You will partner with researchers, engineers, PMs, and compliance to deliver scalable, cost-efficient AI capabilities and enterprise-grade reliability.