Ability to rack, stack, cable, and configure physical servers and multi-node GPU systems from end to end.
Configure HPC and AI environments, including job schedulers (e.g., Slurm), multi-user login environments, and cluster management software (e.g., Warewulf, NVIDIA Base Command, RunAI).
Implement and fine-tune high-speed interconnects (e.g., NVLink, NVSwitch, InfiniBand/NDR) crucial for large-scale distributed training.
Configure and manage large-scale, high-performance storage platforms in the multiple petabytes range, optimized for AI/ML data access patterns.
Install, configure, and maintain the application stack on HPC clusters, including traditional simulation software (StarCCM+, Ansys, Matlab) and the core AI/ML software stack (NVIDIA drivers, CUDA, PyTorch, TensorFlow).
Implement and manage GPU virtualization and sharing technologies, such as Multi-Instance GPU (MIG), to maximize resource utilization across diverse workloads.
Troubleshoot complex, system-wide issues related to application performance, user access, compute nodes, storage, and job queueing services.
Utilize NVIDIA Data Center GPU Manager (DCGM) and additional tools to proactively monitor GPU health and performance, diagnosing and resolving training bottlenecks in collaboration with ML engineers.
Ensure the security and integrity of the server and cluster infrastructure through regular audits, patching, and proactive security measures.
Collaborate closely with engineering and AI/ML research stakeholders to gather requirements and architect robust, scalable solutions.
Manage the hardware lifecycle, from quoting and procuring hardware from vendors to creating and executing deployment schedules.
Provide technical guidance, mentoring, and architectural leadership to other team members.
REQUIRED QUALIFICATIONS
5+ years of experience in designing, developing, and implementing large scale compute enterprise systems and solutions
Strong Knowledge and experience with High Performance Computing concepts to include cluster architecture file system, and high-speed infiniBand/ethernet interconnections
Proven expertise in one or more of the following, Red Hat Enterprise Linux, Ubuntu, HPC, GPU, Azure or AWS cloud services
Strong understanding and experience with systems automation tools (Ansible, Salt, Puppet)
Experience in HPC technologies such as parallel/distribution file systems (e.g., Lustre, GPFS, Pure, VAST)
Working knowledge of HPC batch schedule software (e.g., PBSPro, SLURM)
AWS/Azure experience building HPC clusters
Ability to lift 50 lbs
Eligible to obtain an maintain a US Top Secret Clearance
US Salary Range
$147,000—$196,000 USD
The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:
Benefits
At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next. For more information, Explore Our Benefits.
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