GPU Infrastructure Engineer

Location: San Francisco or remote within the United States

Salary: $150,000–$300,000 per year plus equity incentives

Company

Builds an open superintelligence stack combining compute, environments, evaluations, secure sandboxes, training, and deployment for frontier AI teams.

What you will do

• Build automated discovery, network boot, OS imaging, and configuration workflows for GPU servers.
• Automate BIOS, BMC, NIC, GPU driver, and firmware configuration with staged rollouts and recovery paths.
• Develop hardware inventory and lifecycle services covering machine identity, configuration, health, and readiness.
• Create acceptance tests and burn-in workflows for GPUs, memory, storage, and interconnects.
• Integrate provisioning and health checks with SLURM, Kubernetes, and compute allocation systems.
• Build observability, quarantine, repair, re-provisioning, secure credential handling, tenant isolation, and data sanitization workflows.

Requirements

• 3+ years of experience operating Linux servers or building bare-metal infrastructure automation in production.
• Hands-on experience with PXE/iPXE, DHCP, image provisioning, and out-of-band management such as Redfish or IPMI.
• Strong software engineering and debugging skills in Python, Go, or a comparable language, plus Bash.
• Experience designing reliable automation that handles partial failures, retries, and configuration drift.
• Knowledge of Linux boot, systemd, kernel and driver troubleshooting, OS image management, networking fundamentals, and configuration management.
• Ability to own operational incidents and collaborate across hardware, networking, platform, and datacenter teams.

Nice to have

• Experience with large NVIDIA GPU fleets, DGX/HGX platforms, or heterogeneous server vendors.
• Experience with MAAS, Ironic, Tinkerbell, or similar provisioning systems.
• Experience integrating Kubernetes or SLURM with node lifecycle management.
• Experience with hardware qualification, automated burn-in, fleet health scoring, or open-source infrastructure tooling.

Culture & Benefits

• Work directly with customers building foundation-model training and large-scale inference infrastructure.
• Collaborate across engineering, hardware, networking, platform, and datacenter teams.
• Contribute to open frontier AI infrastructure and systems operating at planetary scale.
• Receive cash compensation plus equity incentives.