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Senior AI Infrastructure Engineer, Physical Infrastructure

Anduril· Corporate Technology : Infrastructure Engineering : Corporate Infrastructure
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Costa Mesa, CA$166k - $220kfull-timePosted 1mo ago

About the role

Senior level role responsible for vision, execution, and long-term stability of GPU-based AI training infrastructure at scale, with a focus on automated resilience, high-performance interconnects, and orchestration across Kubernetes, Run:AI, and Ray.

Responsibilities

  • Rack, stack, cable, and bring up GPU compute (H200/B200/B300, NVL72) including physical topology, power, cooling, firmware/BIOS, and burn in validation.
  • Build and tune the interconnect fabric (NVLink, InfiniBand, RoCE, Spectrum-X) connecting hundreds of GPUs into low latency training and inference clusters.
  • Integrate high performance parallel storage (VAST, DDN, Weka) to sustain throughput for distributed training and terabyte scale multimodal datasets.
  • Automate cluster deployment and configuration end to end, including infrastructure as code for bring up, firmware/driver management, and fabric config.
  • Operate and extend Kubernetes/Run:AI environment for GPU scheduling, quota management, and multi-tenant workload isolation.
  • Own fleet health: monitoring, alerting, and rapid triage of hardware and network faults.
  • Onboard engineers and researchers onto the platform and collaborate to debug, train, and optimize workloads when infrastructure is the bottleneck.
  • Partner with product teams to translate compute needs into platform capabilities.

Qualifications

  • 10+ years in a hands on infrastructure, HPC, or datacenter engineering role supporting GPU compute at scale.
  • Hands on experience with H200/B200/B300 (or comparable) GPU systems: bring up, cabling, firmware/driver management.
  • Experience with high performance interconnects (NVLink, InfiniBand, RoCE, Spectrum-X) in clusters of hundreds of GPUs.
  • Experience with high performance parallel storage (VAST, DDN, Weka, Lustre, or similar).
  • Kubernetes required; Run:ai or similar GPU scheduling/orchestration experience strongly preferred.
  • Strong automation background. You build repeatable, automated deployment pipelines rather than manual processes.
  • Able to lift/move 50+ lbs and perform physical datacenter work (rack/stack/cable/troubleshoot).
  • Eligible to obtain and maintain an active U.S. Top Secret clearance.

Skills

Required:GPU compute hardware managementHigh performance interconnectsKubernetesAutomation / IaC
Nice to have:Run:AI / GPU scheduling

Benefits

  • Top-tier benefits for full-time employees; comprehensive, competitive benefits package
Last updated Sep 9, 2026. Interested? Apply on the company site.

About Anduril

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