Senior Platform Engineer, AI Compute & GPU Kubernetes

AItoolnavio

San Diego (CA)

On-site

USD 170,000 - 250,000

Full time

3 days ago

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Job summary

Shield AI seeks a Platform Engineer to simplify and strengthen the AI Factory compute platform. You will enable GPU workloads on Kubernetes, design sharing policies for multiple teams, and automate deployments using Terraform and Helm.

The role blends software and platform engineering to improve reliability and scalability for ML workloads. You’ll work with ML engineers to translate recurring issues into durable platform capabilities, delivering repeatable installs across cloud, on-premises, and

Qualifications

Experience building and supporting production Kubernetes platforms for GPU workloads.
Strong software experience in Python or Go.
Experience automating infrastructure deployment and upgrades.
Practical Linux, networking and storage troubleshooting skills.
Experience with shared resource scheduling and workload isolation.
Ability to collaborate with ML engineers to address recurring issues.

Responsibilities

Build and maintain software and configuration to run GPU workloads on Kubernetes.
Design quotas, scheduling priorities, permissions and isolation for multi-team use.
Automate deployment and upgrades of GPU services with IaC tools.
Investigate job delays, failures and optimize scheduling and networking.
Develop diagnostics linking queue times, GPU utilization and throughput.
Benchmark workloads and advise on capacity expansion and hardware fit.
Deliver repeatable installations across cloud, on-premises, and air-gapped environments.