Software Engineer: ML Infra

Generalist • San Francisco, CA

21h

About The Position

Generalist trains very large robot foundation models. This requires utilizing very large numbers of the latest generation GPU hardware and infrastructure (currently Nvidia) to run distributed training jobs and researcher experiments. We have extreme requirements on storage and data loading infrastructure that requires maximizing cloud infrastructure and custom solutions. You will also own inference infrastructure. For our robots this is a fleet of on-prem GPUs attached to robots that have extreme real-time and latency budgets in compute constrained environments.

Requirements

• Managed large fleets of GPUs doing large-scale, long-term, highly distributed training runs or inference
• Deep experience in Slurm or Kubernetes for ML workload orchestration
• Build high-scale ML data loaders and preparation systems
• Deeply understand every layer of the ML hardware, storage, and networking stacks
• Experience in the NVidia GPU ecosystem

Responsibilities

• Owning our GPU compute fleets
• Ensure our GPUs are easy for researchers to use and maximally utilized
• Optimizing and improving ML data loading transport and storage in highly distributed fully utilized environments.
• Orchestration of robot inference fleets

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed