HPC Systems Engineer

Anduril • Costa Mesa, CA

13h

About The Position

Anduril is seeking a High Performance Computing (HPC) Systems Engineer to support sensitive programs and help build and maintain large-scale HPC infrastructure. The role supports systems deployed globally for national security missions and involves working with engineering and cybersecurity professionals in a fast-paced, customer-focused environment.

The engineer will design, deploy, configure, and maintain advanced GPU infrastructure and HPC/AI environments, including NVIDIA hardware, high-speed interconnects, large-scale storage, cluster management tools, and application software. The role also includes monitoring and troubleshooting cluster performance and health, maintaining infrastructure security, collaborating with research and engineering stakeholders, managing hardware procurement and deployment, and providing technical leadership to teammates.

Requirements

• At least 5 years of experience designing, developing, and implementing large-scale compute enterprise systems and solutions.
• Strong knowledge and experience with HPC concepts, including cluster architecture, file systems, and high-speed InfiniBand/Ethernet interconnections.
• Proven expertise in one or more of Red Hat Enterprise Linux, Ubuntu, HPC, GPU, Azure, or AWS cloud services.
• Strong understanding and experience with systems automation tools such as Ansible, Salt, or Puppet.
• Experience with HPC technologies such as parallel/distributed file systems, including Lustre, GPFS, Pure, or VAST.
• Working knowledge of HPC batch scheduling software such as PBSPro or SLURM.
• AWS or Azure experience building HPC clusters.
• Ability to lift 50 lbs.
• Eligibility to obtain and maintain a US Top Secret Clearance.

Responsibilities

• Support high-profile operational and research requirements in a fast-paced, customer-focused environment.
• Lead the design, deployment, and lifecycle management of advanced NVIDIA GPU infrastructure, including H100, H200, and B200/B300 systems.
• Rack, stack, cable, and configure physical servers and multi-node GPU systems.
• Configure HPC and AI environments, including job schedulers, multi-user login environments, and cluster management software.
• Implement and fine-tune high-speed interconnects such as NVLink, NVSwitch, and InfiniBand/NDR.
• Configure and manage large-scale, high-performance storage platforms optimized for AI/ML data access patterns.
• Install, configure, and maintain traditional simulation and AI/ML application software on HPC clusters.
• Implement and manage GPU virtualization and sharing technologies, including Multi-Instance GPU (MIG).
• Troubleshoot system-wide issues involving application performance, user access, compute nodes, storage, and job queueing services.
• Use NVIDIA Data Center GPU Manager (DCGM) and other tools to monitor GPU health and performance, and diagnose training bottlenecks with ML engineers.
• Maintain server and cluster security through audits, patching, and proactive security measures.
• Collaborate with engineering and AI/ML research stakeholders to gather requirements and design scalable solutions.
• Manage the hardware lifecycle, including vendor quoting and procurement and deployment scheduling.
• Provide technical guidance, mentoring, and architectural leadership to team members.

Benefits

• Highly competitive equity grants are included in the majority of full-time offers.
• Top-tier benefits for full-time employees, described as comprehensive and competitive and available at little to no cost to employees.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed