Robotics ML Infrastructure Engineer: GPU Fleet & Inference

Generalist AI, Inc.; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Generalist AI, Inc. in San Francisco is seeking an Infrastructure Engineer for GPU compute and robotics ML workloads.

You will own our GPU fleets and ensure researchers can run large-scale training and inference with low latency on on-prem hardware. The role requires deep expertise in Slurm and Kubernetes for ML workloads, plus hands-on experience with the Nvidia GPU ecosystem, distributed data loading, and storage.

Qualifications

• Experience managing large GPU fleets for long-running ML workloads.
• Strong knowledge of distributed ML systems and orchestration tools.
• Experience with ML data loading, storage, and transport in distributed environments.
• Deep understanding of ML hardware, software, and networking stacks.

Responsibilities

• Own our GPU compute fleets.
• Ensure GPUs are easy to use and maximally utilized by researchers.
• Optimize data loading, transport, and storage in distributed environments.
• Orchestrate robot inference fleets.

Skills

Fleet management

Distributed ML workloads

ML data loading optimization

Real-time inference optimization

Tools

Slurm

Kubernetes

NVidia GPU ecosystem

Job description

Generalist AI, Inc. in San Francisco is seeking an Infrastructure Engineer for GPU compute and robotics ML workloads.

You will own our GPU fleets and ensure researchers can run large-scale training and inference with low latency on on-prem hardware. The role requires deep expertise in Slurm and Kubernetes for ML workloads, plus hands-on experience with the Nvidia GPU ecosystem, distributed data loading, and storage.