GPU Systems Engineer 4

RPMGlobal; Bethesda (MD); On-site; USD 140,000 - 190,000; Full time

Job summary

RPMGlobal seeks a senior systems engineer to design, deploy, and optimize GPU clusters for enterprise AI mission systems in a secure government environment.

The role emphasizes operating systems, hardware, NVIDIA platforms (DGX/HGX/H200/H100/L4s), and high-speed networking, with Linux configuration, automation, and performance analysis at the core. Active TS/SCI clearance is required.

Qualifications

• Active TS/SCI with ability to obtain a CI Polygraph.
• Bachelor's degree with 10 years of experience in the field.
• Experience managing NVIDIA GPU data center platforms (DGX, HGX, H200, H100, L4s).
• Knowledge of enterprise server components, including storage/network controllers, HBAs, and SSDs.
• Strong Linux distributions expertise (RHEL, Ubuntu, Oracle, Rocky).
• Excellent problem-solving and teamwork capabilities.
• Meets DoD 8570.11 IAT Level II certification; Level III acceptable.
• U.S. citizenship is required.

Responsibilities

• Design, configure, and maintain GPU clusters.
• Collaborate with multidisciplinary teams to define architectures for performance and power efficiency.
• Integrate GPUs with Linux-based systems for AI/ML workflows.
• Optimize GPU drivers for reliability and performance.
• Analyze GPU performance to identify bottlenecks and improve cross-layer efficiency.
• Develop debugging tools, profiling utilities, and performance analysis software for Linux.
• Leverage Bash, Python, Ansible, Puppet, and Salt for tooling and automation.
• Maintain architectural specifications and Linux best practices.
• Support ATO activities and ensure compliance with federal security standards.

Skills

NVIDIA GPUs

Linux admin

Python automation

Shell scripting

Security clearance

Team collaboration

Performance optimization

Education

Bachelor's degree

Master's degree

PhD

Tools

Kubernetes

Argo

Airflow

Kubeflow

Prometheus

Grafana

Slurm

LSF

Job description

Position Summary

Support enterprise AI mission systems by designing, developing, and optimizing GPU clusters, with deep focus on operating systems, hardware, GPU platforms, and high-speed networking in a secure customer environment.

Essential Duties and Responsibilities

• Design, configure, and maintain GPU clusters.
• Collaborate with a multidisciplinary team to define and optimize architectures for performance, power efficiency, and required features.
• Work closely with AI/ML engineers to integrate GPUs with Linux-based systems.
• Optimize GPU drivers for compatibility, reliability, and performance.
• Analyze GPU performance, identify bottlenecks, and develop strategies to improve efficiency across hardware and software layers.
• Build and maintain debugging tools, profiling utilities, and performance analysis software for Linux environments.
• Leverage Bash, Python, Ansible, Puppet, and Salt for tooling and automation.
• Maintain technical documentation, architectural specifications, and Linux best practices.
• Support ATO activities and ensure compliance with federal security standards.

Required Qualifications

• Active TS/SCI with ability to obtain a CI Polygraph.
• Bachelor's degree with a minimum of ten years of experience in the category field.
• Experience managing NVIDIA GPU data center platforms, including DGX, HGX, H200, H100, and L4s.
• Knowledge of enterprise server components, including storage/network controllers, HBAs, and SSDs.
• Strong expertise with Linux distributions, including RHEL, Ubuntu, Oracle, and Rocky.
• Excellent problem-solving skills and the ability to collaborate within a team.
• Meet DoD 8570.11 IAT Level II certification requirements at a minimum; IAT Level III is also acceptable.
• U.S. citizenship is required due to the nature of the government contracts supported.

Preferred Qualifications

• Experience with Kubernetes cluster management and AI/ML workflow orchestration, including Argo, Airflow, and Kubeflow.
• Familiarity with GPU virtualization and cloud computing.
• Experience with Prometheus and Grafana for monitoring.
• Knowledge of distributed resource scheduling systems such as Slurm, LSF, or similar tools.

Required Education and Experience Equivalency

• Bachelors' Degree with 10 years of experience.
• Masters' Degree with 10 years of experience.
• PhD with 10 years of experience.

RequiredCertifications

• DoD 8570.11 IAT Level II certification: Security+ CE, CCNA-Security, GICSP, GSEC, or SSCP.

Required Security Clearance

• Active TS/SCI with ability to obtain a CI Polygraph.