Staff Platform Engineer AI Compute

Skills

About the Role

You will build and maintain Kubernetes-based GPU compute platforms. You will automate deployments, troubleshoot workload and infrastructure issues, improve scheduling and access controls, create diagnostics, and use workload benchmarks to guide capacity and hardware decisions.

Requirements

• Experience building and supporting production Kubernetes platforms with GPU or distributed-computing workloads
• Software engineering skills in Python, Go, or a comparable language
• Experience automating infrastructure deployment, configuration, and upgrades
• Linux, networking, and storage troubleshooting skills
• Experience with shared-resource scheduling, access controls, or workload isolation
• Ability to work with machine-learning engineers and translate recurring problems into platform capabilities

Responsibilities

• Build and maintain software and configuration for GPU workloads on Kubernetes
• Design quotas, scheduling priorities, permissions, and workload isolation
• Automate GPU service deployment and upgrades using infrastructure as code, Terraform, and Helm
• Troubleshoot scheduling, configuration, storage, and networking issues
• Build diagnostics for queue times, GPU utilization, memory requirements, and training throughput
• Benchmark workloads and recommend GPU capacity and hardware
• Deliver repeatable installations across cloud, on-premises, and air-gapped environments

Benefits

• Bonus
• Benefits
• Equity