Senior GPU Compute Architect for AI Infrastructure

Flexion Robotics; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

401(k) with company contributions

Health, dental & vision coverage

Open PTO policy & paid company holid​a

Relocation and visa sponsorship (Zurih

Job summary

Flexion Robotics is seeking a senior ML engineer to own and optimize its GPU compute platforms on-site in San Francisco. You will design, bring up, operate, and optimize large GPU clusters and collaborate with AI engineers to improve training speed and hardware utilization.

You will influence compute strategy, implement scalable ML pipelines, and work with leadership and infrastructure teams to advance Flexion’s ambitious AI roadmap.

Qualifications

• Degree in Computer Science, Electrical Engineering or Software Engineering (or equivalent practical experience).
• Hands-on experience with training or inference of large models (billions of parameters) on distributed multi-node GPU hardware.
• Proficiency in Python and working knowledge of PyTorch.
• Deep understanding of distributed training concepts (DDP, FSDP, NCCL).
• Experience with at least one cloud platform (AWS, GCP, Azure) or large-scale on-premises GPU infrastructure.
• Experience with job scheduling and orchestration tools: Slurm and/or Kubernetes/KubeRay.

Responsibilities

• Architect, run and continuously improve existing and future cloud-based GPU clusters.
• Help AI engineers optimize training workloads and maximize hardware utilization.
• Contribute to short- and long-term GPU compute strategies in collaboration with AI engineering teams.
• Optimize capacity and cost by exploring multi-cloud strategies and evaluating trade-offs.
• Raise the bar on engineering practices, including testing, code quality, documentation, and system reliability.
• Collaborate with leadership and infrastructure teams to execute the roadmap.

Skills

Python

PyTorch

Distributed training concepts

DDP / FSDP

NCCL

Slurm

Kubernetes

Cloud platforms (AWS/GCP/Azure)

Education

Degree in Computer Science or Electrical Engineering or Software Engineering

Tools

Slurm

Kubernetes

KubeRay

Terraform

Ansible

Lustre

PyTorch Profiler

Job description

Flexion Robotics is seeking a senior ML engineer to own and optimize its GPU compute platforms on-site in San Francisco. You will design, bring up, operate, and optimize large GPU clusters and collaborate with AI engineers to improve training speed and hardware utilization.

You will influence compute strategy, implement scalable ML pipelines, and work with leadership and infrastructure teams to advance Flexion’s ambitious AI roadmap.