High Compute Engineer

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.

• 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.

• 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).

• 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.

• 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).

• 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.