Job Description

Description

At Leidos, we deliver innovative solutions through the efforts of our diverse and talented people who are dedicated to our customers’ success. We empower our teams, contribute to our communities, and operate sustainable practices. Everything we do is built on a commitment to do the right thing for our customers, our people, and our community. Our Mission, Vision, and Values guide the way we do business. Employees enjoy career enrichment opportunities available through mobility and development and experience rewarding relationships with supportive supervisors and talented colleagues and customers. Your most important work is ahead.

 

If this sounds like the kind of environment where you can thrive, keep reading!

We are seeking a forward-leaning High Compute Engineer to lead the design, optimization, and integration of GPU-centric high-performance compute environments. The ideal candidate will be responsible for managing existing NVIDIA A100 and DGX-1 systems while designing scalable architectures to incorporate emerging GPU hardware as mission demands evolve.

This role is critical to our advanced compute initiatives, where performance, stability, and future-readiness drive every architectural decision. You'll work cross-functionally with data scientists, AI/ML developers, cybersecurity experts, and infrastructure teams to create a robust, secure, and performant GPU compute ecosystem.

This is a 100% on-site position. All work must be performed at the customer site in Bethesda at the Intelligence Community Campus.

Responsibilities:

• Manage, optimize, and monitor existing high-performance GPU systems including NVIDIA A100s and DGX-1 platforms.

• Architect integration plans for scaling GPU compute infrastructure, including newer platforms (e.g., H100, Grace Hopper, AMD Instinct).

• Collaborate with data science teams to fine-tune GPU workloads for AI/ML pipelines.

• Design and implement high-speed networking (InfiniBand/RDMA) and storage solutions optimized for GPU data flow.

• Develop automation workflows using infrastructure-as-code (IaC) tools (e.g., Ansible, Terraform, SaltStack).

• Ensure system security, compliance, and patch management in alignment with NIST, RMF, or agency-specific controls.

• Analyze compute performance metrics and provide strategic recommendations for system enhancements.

• Maintain documentation on system architectures, configurations, and operational procedures.

You Bring

• Bachelor's or higher degree in Computer Engineering, Computer Science, or a related field with at least 12 years of related technical experience. Additional years of experience may be considered in lieu of a degree.

• 5+ years experience supporting GPU compute environments in mission-critical or enterprise settings.

• Proficiency with NVIDIA technologies: A100, DGX-1, CUDA, cuDNN, NCCL.

• Strong background in Linux (RHEL/CentOS/Ubuntu), kernel tuning, and HPC stack deployment.

• Experience with containerized GPU workloads using Docker, Kubernetes, and NVIDIA GPU Operator.

• Familiarity with distributed compute frameworks (e.g., SLURM, Kubernetes, Ray).

• Strong scripting skills: Bash, Python, or similar.

• Proven ability to plan and execute large-scale system upgrades and migrations.

• Candidate must, at a minimum, meet DoD 8570.11- IAT Level II certification requirements (currently Security+ CE, CCNA-Security, GICSP, GSEC, or SSCP along with an appropriate computing environment (CE) certification). An IAT Level III certification would also be acceptable (CASP+, CCNP Security, CISA, CISSP, GCED, GCIH, CCSP).

Clearance

• Active TS/SCI clearance with Polygraph required OR active TS/SCI and willingness to obtain and maintain a Poly.

• US Citizenship is required due to the nature of the government contracts we support.

Preferred Qualifications

• Experience with hybrid cloud GPU environments (AWS, GCP, or Azure with NVIDIA support).

• Familiarity with AI/ML tooling such as PyTorch, TensorFlow, ONNX, and RAPIDS.

• Experience integrating GPUs with storage systems (e.g., Lustre, BeeGFS, Ceph).

• Exposure to hardware acceleration platforms (e.g., FPGA, custom ASIC).

Why Join Us

• Shape the future of high-performance computing within a cutting-edge technical team.

• Influence procurement and system design decisions for future GPU investments.

• Work alongside industry leaders in machine learning, cyber operations, and advanced analytics.

• Access to premier NVIDIA hardware in real production environments.

Original Posting:

June 24, 2025

For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

Pay Range $126,100.00 - $227,950.00

The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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