Senior Platform Engineer, AI Compute & GPU Kubernetes

F7d8749a; San Diego (CA); On-site; USD 180,000 - 260,000; Full time

Job summary

Shield AI is seeking a Senior Staff Platform Engineer to optimize the AI Factory compute platform, enabling fast, reliable GPU workloads for ML teams. You will drive performance, capacity planning and reproducible deployments across cloud, on-premises, and air-gapped environments.

You will collaborate with ML engineers to translate workloads into robust platform capabilities, leveraging Kubernetes, Terraform, Helm, Run:ai and related tools to scale our AI infrastructure globally.

Qualifications

• Experience building and supporting production Kubernetes platforms, including GPU workloads.
• Strong software engineering skills in Python, Go, or similar.
• Experience automating infrastructure deployment, configuration and upgrades.
• Practical Linux, networking and storage troubleshooting skills.
• Experience with shared resource scheduling or workload isolation.
• Ability to work with ML engineers to translate workloads into platform capabilities.

Responsibilities

• Build and maintain the software and configuration that let developers run GPU workloads on Kubernetes.
• Design quotas, scheduling priorities, permissions and isolation for multi-team access.
• Automate deployment and upgrades of GPU services, including Run:ai, with Terraform and Helm.
• Investigate why jobs wait, fail or run slowly, and fix recurring issues.
• Build diagnostics linking queue times, GPU utilization, memory needs and training throughput to user experience.
• Benchmark workloads and advise on capacity expansion and hardware fit.
• Deliver repeatable installations across cloud, on-premises and air-gapped environments.

Skills

Kubernetes platforms

Python/Go

Infra automation

Linux networking storage

Shared scheduling/isolation

ML workload collaboration

Tools

Terraform

Helm

Run:ai

Ray

PyTorch

Job description

Shield AI is seeking a Senior Staff Platform Engineer to optimize the AI Factory compute platform, enabling fast, reliable GPU workloads for ML teams. You will drive performance, capacity planning and reproducible deployments across cloud, on-premises, and air-gapped environments.

You will collaborate with ML engineers to translate workloads into robust platform capabilities, leveraging Kubernetes, Terraform, Helm, Run:ai and related tools to scale our AI infrastructure globally.