Staff, Platform Engineer AI Compute (6034)

The role

This person will build, maintain and automate the shared GPU compute platform that machine-learning engineers use to train and evaluate models. The work covers Kubernetes, scheduling, quotas, diagnostics and capacity planning.

What you will do

• 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.

Required 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.

Nice to have

• Experience with Run:ai or comparable GPU scheduling and resource-management systems.
• Familiarity with distributed training and tools such as Ray or PyTorch.
• Experience delivering on-premises or air-gapped platforms, or contributing to open-source infrastructure.

Benefits

• Bonus
• Equity
• Benefits package (full-time regular employees; not for part-time employees or military fellows)
• Temporary benefits package after 60 days of employment (temporary employees)

Before you apply

• All offers are contingent on a cleared background check and possible reference check.
• Salary depends on factors such as skill set, experience, licenses and certifications, and work location.
• Speak to a talent acquisition representative for more information on the offer.

About the company

Shield AI is a venture-backed defense-tech company that builds intelligent systems to protect service members and civilians. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation technologies.