3 days ago
Base Salary
$200k - $300k/yr
Responsibilities
- Build and maintain software and configuration for running GPU workloads on Kubernetes.
- Design quotas, scheduling priorities, permissions, and isolation for shared compute environments.
- Automate deployment and upgrades of GPU services, including Run:ai, using Terraform and Helm.
- Investigate and resolve scheduling, configuration, storage, networking, and workload performance issues.
- Build diagnostics connecting queue times, GPU utilization, memory requirements, and training throughput to developer experience.
- Benchmark workloads and recommend GPU capacity additions and hardware selections.
- Deliver repeatable installations and upgrades across cloud, on-premises, and air-gapped environments.
- Develop the reference architecture used by internal engineering teams and customers building AI capabilities.
Requirements
- Experience building and supporting production Kubernetes platforms for 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 and turn recurring problems into maintained platform capabilities.
- Preferred experience with Run:ai or comparable GPU scheduling and resource-management systems.
- Preferred familiarity with distributed training and Ray or PyTorch.
- Preferred experience delivering on-premises or air-gapped platforms or contributing to open-source infrastructure.
Benefits
- Full-time regular employee offer package includes bonus, benefits, and equity in addition to pay within the listed range.
- Temporary employees receive a temporary benefits package applicable after 60 days of employment.
- Offers are contingent on a cleared background and possible reference check.
- Military fellows and part-time employees are not eligible for benefits.
- Shield AI is an equal opportunity and affirmative action employer.
About Shield AI
Shield AI builds autonomous systems for military and national security customers, combining its Hivemind autonomy software with V-BAT and X-BAT unmanned aircraft and Aechelon simulation technologies. The privately held company sells hardware, software, and related services to U.S. and allied defense agencies. Founded in 2015 and headquartered in San Diego, it operates across the U.S., Europe, the Middle East, and Asia-Pacific, and its technology is used in operational deployments.