HPC AI/ML Platform Engineer

TEKsystems • Seattle, WA

9d • $100 - $100 • Remote

About The Position

TEKsystems Global Services is seeking experienced HPC AI/ML Platform Engineers to support one of the world's largest AI compute environments. The team operates and scales multi-cloud infrastructure for GPU-intensive model training, deep learning research, and production AI workloads across AWS, CoreWeave, GCP, OCI, and other emerging compute providers. This is a specialized infrastructure role focused on High-Performance Computing (HPC), deep learning platforms, large-scale GPU environments, and AI/ML training infrastructure where performance, reliability, and efficient resource utilization are critical.

The engineer will help provision and operate large-scale compute environments, manage Kubernetes-based infrastructure, optimize GPU resource allocation, support Slurm scheduling systems, and build automation that enables rapid AI platform growth. The role supports production environments for AI model development, training, and inference workloads at significant scale. This is a contract position based in Seattle, Washington, and is fully remote.

Requirements

• At least 4 years supporting HPC, AI/ML infrastructure, machine learning platforms, or deep learning environments.
• Strong experience with distributed compute, GPU infrastructure, or large-scale training environments.
• Hands-on Kubernetes experience at scale, including cluster lifecycle management, scheduler troubleshooting, node pool management, networking and CNI troubleshooting, and production upgrades across large fleets.
• Terraform experience building and managing infrastructure through Infrastructure as Code.
• Python experience for platform automation and operational tooling.
• Working knowledge of AWS services including EC2, S3, EFS, and FSx for Lustre.

Nice To Haves

• Experience with Slurm job scheduling.
• Experience supporting machine learning training, inference, deep learning, large language model (LLM), or GPU-intensive workloads.

Responsibilities

• Provision and operate large-scale compute environments.
• Manage Kubernetes-based infrastructure, including cluster lifecycle, schedulers, node pools, networking, CNI, and production upgrades across large fleets.
• Optimize GPU resource allocation.
• Support Slurm scheduling systems.
• Build automation and operational tooling to enable rapid AI platform growth.
• Support production environments for AI model development, training, and inference workloads.

Benefits

• Medical, dental, and vision coverage, if eligible.
• Critical illness, accident, and hospital coverage, if eligible.
• 401(k) retirement plan with pre-tax and Roth post-tax contributions available, if eligible.
• Voluntary life and AD&D insurance for the employee and dependents, if eligible.
• Short- and long-term disability coverage, if eligible.
• Health Spending Account (HSA), if eligible.
• Transportation benefits, if eligible.
• Employee Assistance Program, if eligible.
• Time off/leave, including PTO, vacation, or sick leave, if eligible.

What This Job Offers

• Career Level: Mid Level
• Education Level: No Education Listed