Platform Engineer, AI Compute & GPU on Kubernetes

Shield; San Diego (CA); On-site; USD 200,000 - 300,000; Full time

Job summary

Shield AI's AI Factory is seeking a Senior Staff Platform Engineer in San Diego to simplify and scale GPU compute for ML workloads across cloud, on‑premises and air‑gapped environments.

You will build and maintain the Kubernetes‑based platform, automate deployments with Terraform and Helm, optimize scheduling, and help developers troubleshoot workloads to improve throughput.

This hands‑on role shapes how researchers iterate and how AI systems move from experimentation to production at Shield AI.

Qualifications

• Experience building and supporting production Kubernetes platforms, including GPU or distributed computing workloads.
• Strong software engineering skills in Python, Go or a comparable language.
• Experience automating infrastructure deployment, configuration and upgrades.
• Practical Linux, networking and storage troubleshooting skills.
• Experience with shared resource scheduling, access controls or workload isolation.
• Ability to work directly with machine-learning engineers, understand their workloads and turn recurring problems into maintained 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 so multiple teams can share compute predictably.
• Automate deployment and upgrades of GPU services, including Run:ai, with infrastructure as code and tools such as Terraform and Helm.
• Investigate why jobs wait, fail or run slowly, and fix recurring scheduling, configuration, storage and networking problems.
• Build diagnostics that connect queue times, GPU utilization, memory requirements and training throughput to the developer’s experience.
• Benchmark representative workloads and recommend when to add GPU capacity, how much to add and which hardware fits the workload.
• Deliver repeatable installations and upgrades across cloud, on-premises and air-gapped environments.

Skills

Kubernetes platforms

Python/Go

Infrastructure automation

Linux networking storage

Resource scheduling

Collaboration with ML engineers

Tools

Terraform

Helm

Run:ai

Ray

PyTorch

Job description

Shield AI's AI Factory is seeking a Senior Staff Platform Engineer in San Diego to simplify and scale GPU compute for ML workloads across cloud, on‑premises and air‑gapped environments.

You will build and maintain the Kubernetes‑based platform, automate deployments with Terraform and Helm, optimize scheduling, and help developers troubleshoot workloads to improve throughput.

This hands‑on role shapes how researchers iterate and how AI systems move from experimentation to production at Shield AI.