Senior AI Infrastructure Engineer, Physical Infrastructure

The role

You will lead the vision, execution, and long-term stability of GPU training at scale. You will build self-healing mechanisms, tune high-speed networking, and optimize scheduling to ensure cluster robustness for ML platform and research teams.

What you will do

• Rack, stack, cable, and bring up GPU compute including physical topology, power, cooling, firmware/BIOS, and burn in validation.
• Build and tune the interconnect fabric connecting hundreds of GPUs into low latency training and inference clusters.
• Integrate high performance parallel storage to sustain throughput for distributed training and multi modal datasets.
• Automate cluster deployment and configuration end to end using infrastructure as code.
• Operate and extend the Kubernetes/Run:AI environment for GPU scheduling and multi tenant workload isolation.
• Own fleet health through monitoring, alerting, and rapid triage of hardware and network faults.
• Onboard engineers and researchers onto the platform and act as an escalation point for debugging workloads.
• Partner with product facing teams to translate emerging compute needs into platform capability.

Required 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.
• Strong automation background.
• 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.

Nice to have

• Run:ai or similar GPU scheduling/orchestration experience
• Experience with NVIDIA NVL72 rack scale systems.
• Experience supporting LLM token serving/inference infrastructure alongside training clusters.
• Network fabric tuning experience (congestion control, adaptive routing, QoS) for RoCE/InfiniBand at scale.
• Familiarity with GPU/network observability tooling (DCGM, fabric telemetry) and automated fault detection.
• Experience supporting infrastructure as a shared platform serving multiple internal customer teams with differing requirements.

Benefits

• Comprehensive, competitive benefits package available at little to no cost to employees

Before you apply

• Eligible to obtain and maintain an active U.S. Top Secret clearance.
• By submitting your application, you consent to Anduril Industries using a third-party service provider to conduct pre-employment risk, integrity, and due diligence screening.

About the company

Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. Their family of systems is powered by Lattice OS, an AI-powered operating system.