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GPU Platform Infrastructure Engineer
Job in
Warren, Macomb County, Michigan, 48091, USA
Listed on 2026-06-07
Listing for:
Optimal
Full Time
position Listed on 2026-06-07
Job specializations:
-
IT/Tech
Systems Engineer, AI Engineer
Job Description & How to Apply Below
Job Title:
GPU Platform Infrastructure Engineer
Support the GM ARC RTD team by building and maintaining the foundational GPU cluster platform infrastructure supporting shared AI/ML, simulation, and validation workloads. This role focuses on GPU access governance, resource allocation, scheduling policies, observability, and operational support for multi-tenant GPU environments including RTX 6000, A100, B200, and future systems.
Required Experience- 3+ years of experience in Platform Engineering, Infrastructure Engineering, Dev Ops, or related field
- Bachelor's or Master's degree in Systems Engineering, Computer Science, Computer Engineering, or related discipline
- Manage GPU cluster access provisioning, onboarding, permissions, and lifecycle management
- Design and maintain GPU resource allocation policies, quotas, namespace isolation, and scheduling configurations
- Develop GPU utilization dashboards, reporting, monitoring, and capacity tracking solutions
- Create reusable job submission templates and onboarding documentation for ML, Isaac Sim simulation, and validation workloads
- Support platform governance, operational continuity, infrastructure scalability, and CI/CD integration
- Design and develop GUI-based tools for streamlined Docker development workflows
- Collaborate with infrastructure, AI/ML, and engineering teams to support shared GPU operations
- Experience with Linux, Kubernetes, Docker, and GPU infrastructure environments
- Knowledge of workload scheduling, resource management, and multi-tenant platform operations
- Experience supporting AI/ML, simulation, or GPU-intensive engineering workloads
- Experience with monitoring, observability, and reporting tools
- Strong scripting and automation skills using Python, Bash, or similar languages
- Familiarity with NVIDIA GPU platforms, containerized compute environments, and infrastructure automation tools
- Experience with CI/CD pipelines and cloud platforms such as AWS, Azure, or GCP is a plus
- Experience with GUI development frameworks is a plus
- Strong troubleshooting, documentation, and operational support skills
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