Senior AI Infrastructure Engineer — GPU Scale & HPC

Anduril; Seattle (WA); On-site; USD 166,000 - 220,000; Full time

Job summary

Anduril Industries in Seattle, WA is seeking a Senior AI Infrastructure Engineer to own and scale GPU training infrastructure. You will lead the vision for robust, fault-tolerant GPU clusters, automate deployments, and enhance observability across research and product teams.

You will optimize NCCL, high-speed networking, and scheduling with Kubernetes, Run:AI, and Ray, ensuring high availability and scalable workflows for ML across the company.

Qualifications

• 10+ years in hands-on infrastructure, HPC, or datacenter engineering supporting GPU compute at scale.
• Hands-on experience with H200/B200/B300 GPUs: bring up, cabling, firmware/driver management.
• Experience with high performance interconnects (NVLink, InfiniBand, RoCE, Spectrum-X) in large GPU clusters.
• Experience with high performance parallel storage (VAST, DDN, Weka, Lustre or similar).
• Kubernetes required; Run:AI or similar GPU scheduling/orchestration experience preferred.
• Strong automation background; build repeatable deployment pipelines, not manual processes.
• Able to lift/move 50+ lbs and perform physical datacenter work.
• Eligible to obtain and maintain an active U.S. Top Secret clearance.

Responsibilities

• Rack, stack, cable, and bring up GPU compute clusters and topology.
• Build and tune interconnect fabric (NVLink, InfiniBand, RoCE) across hundreds of GPUs.
• Integrate high performance storage to sustain throughput for distributed training.
• Automate cluster deployment and configuration end-to-end; IaC for bring-up and fabric config.
• Operate and extend Kubernetes/Run:AI for GPU scheduling and multi-tenant workloads.
• Own fleet health: monitoring, alerting, triage of hardware and network faults.
• Onboard engineers and researchers to the platform; assist with workloads as needed.
• Partner with product teams to translate compute needs into platform capabilities.

Skills

GPU compute at scale

Kubernetes

Automation pipelines

HPC infrastructure

Datacenter operations

Top Secret clearance

Tools

NVIDIA NVL72

Run:AI

Ray scheduling

NVIDIA NVLink/InfiniBand

VAST

Weka

Job description

Anduril Industries in Seattle, WA is seeking a Senior AI Infrastructure Engineer to own and scale GPU training infrastructure. You will lead the vision for robust, fault-tolerant GPU clusters, automate deployments, and enhance observability across research and product teams.

You will optimize NCCL, high-speed networking, and scheduling with Kubernetes, Run:AI, and Ray, ensuring high availability and scalable workflows for ML across the company.