GPU Systems Engineer III — AI Clusters & Linux

RPMGlobal; Bethesda (MD); On-site; USD 120,000 - 260,000; Full time

Job summary

RPMGlobal is seeking a senior, security-cleared engineer to design, deploy, and optimize GPU clusters for enterprise AI mission systems. You will work with Linux-based environments, collaborate with AI/ML teams, and drive performance improvements across hardware and software layers.

Responsibilities include integration with NVIDIA data center platforms, driver optimization, tooling automation, documentation, and ensuring compliance with federal security standards.

Qualifications

• Active TS/SCI clearance with ability to obtain CI Polygraph.
• Bachelor's degree with six years experience or 9 years without a degree.
• Experience managing NVIDIA GPU data center platforms (DGX, HGX, H200, H100, L4s).
• Strong Linux expertise (RHEL, Ubuntu, Oracle, Rocky).
• IAT Level II/III certification requirements.
• U.S. citizenship required for government contracts.

Responsibilities

• Design, configure, and maintain GPU clusters.
• Collaborate to optimize architectures for performance and efficiency.
• Work with AI/ML engineers to integrate GPUs with Linux systems.
• Optimize GPU drivers for reliability and performance.
• Analyze GPU performance and remove bottlenecks across hardware/software.
• Build and maintain debugging tools and performance analysis software for Linux.
• Use Bash, Python, Ansible, Puppet, Salt for tooling/automation.
• Document architectures and Linux best practices.
• Support ATO activities and ensure DoD security compliance.

Skills

Linux administration

Python scripting

Bash scripting

Ansible

Puppet

Salt

Kubernetes

Prometheus

Grafana

Slurm

LSF

Education

Bachelor's Degree

High School Diploma / GED

Associates Degree

Master's Degree

PhD

Tools

NVIDIA DGX

HGX

H200

H100

L4s

DoD 8570.11 IAT certifications

Job description

RPMGlobal is seeking a senior, security-cleared engineer to design, deploy, and optimize GPU clusters for enterprise AI mission systems. You will work with Linux-based environments, collaborate with AI/ML teams, and drive performance improvements across hardware and software layers.

Responsibilities include integration with NVIDIA data center platforms, driver optimization, tooling automation, documentation, and ensuring compliance with federal security standards.