Remote Director, AI Platform & Scale

Capital One

San Jose (CA)

Remote

USD 294,000 - 335,000

Full time

6 days ago
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Job summary

Capital One is seeking a Director of AI Engineering (Remote Eligible) to lead the Generative AI Training platform, overseeing distributed training, RL workflows, and GPU scheduling at scale. You will mentor a multi-disciplinary team, balance build vs buy across Open Source and SaaS, and partner with research, compliance, and risk functions to advance responsible AI.

This role requires strong technical leadership, cloud and GPU infrastructure expertise, and a vision for scalable, cost-efficient

Qualifications

  • Bachelor’s or Master’s in CS/AI/EE/CE with 6+ years AI/ML experience
  • At least 3 years of people leadership experience
  • Experience building and operating large-scale ML/GPU training infrastructure

Responsibilities

  • Deliver AI-powered products with cross-functional teams
  • Oversee core systems: distributed training, RL workflows, scheduling, fault tolerance
  • Make build-vs-buy decisions on Open Source and SaaS tools
  • Scale training efficiency and cost
  • Own GPU capacity planning and quotas
  • Contribute to long-term AI platform roadmap
  • Mentor and develop your team
  • Translate AI strategy into portfolio plans
  • Scale practices with shared infrastructure and governance
  • Establish Responsible AI standards
  • Partner with research, compliance, risk teams

Skills

AI systems leadership
Distributed training
GPU scheduling
Policy and governance

Education

Bachelor's degree in CS/AI/EE/CE (8+ yrs)
Master's degree in CS/AI/EE/CE (6+ yrs)

Tools

AWS
HuggingFace
PyTorch
Kubernetes
KServe
vLLM
DeepSpeed
Megatron

Job description

Capital One is seeking a Director of AI Engineering (Remote Eligible) to lead the Generative AI Training platform, overseeing distributed training, RL workflows, and GPU scheduling at scale. You will mentor a multi-disciplinary team, balance build vs buy across Open Source and SaaS, and partner with research, compliance, and risk functions to advance responsible AI.

This role requires strong technical leadership, cloud and GPU infrastructure expertise, and a vision for scalable, cost-efficient

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