Software Engineer, Compute Infrastructure

What we're looking for

We need a senior or staff-level systems engineer who has personally brought bare-metal GPU capacity, or similar compute, online and kept it running reliably for real users. That includes working with datacenters and vendors. There's no fixed years-of-experience requirement. Exceptional new graduates will be considered only if they show substantial, relevant hands-on work. You must be skilled at Kubernetes in practice: provisioning, automating, debugging and operating a production cluster, and writing and understanding its code and configuration. You should be comfortable owning hands-on deployment and production operations as the first engineer and technical lead of a new compute infrastructure team. You should also have a track record of measurable reliability and customer results. Bonus points for Slurm scheduling and accounting, Environment Modules (module load), shared Python/CUDA environments, configuration management, infrastructure as code, modern toolchains such as uv, NVIDIA GPU systems, InfiniBand/RoCE, or virtualization (KVM, QEMU, device passthrough).

What you'll do

• Bring GPU capacity online by working with datacenter operators, hardware vendors and onsite technicians to turn delivered servers into usable capacity. This covers racking, power, cooling, cabling, networking and remote management. The goal is to have GPUs online by the end of November 2026.
• Take ownership of the first bare-metal GPU service, which customers access over SSH. Make practical, incremental progress with a simple service before building a larger software platform.
• Provision, automate, debug and operate production Kubernetes and server fleets, including cluster and node lifecycle, networking, storage, capacity, upgrades, observability and incident response.
• Run Linux systems administration and SRE work: user and SSH access, system services, package and configuration management, patching, diagnostics, reliability and recovery. Automate provisioning, OS images, firmware, drivers and configuration step by step.
• Set up acceptance tests that check GPUs, memory, storage and network performance before machines join the fleet. Build monitoring and diagnostics that detect, isolate and recover unhealthy nodes.
• Coordinate repairs and replacements with vendors, lead incident investigations, and turn recurring failures into software fixes. Make upgrades, maintenance and recovery safe and easy to understand.
• As needs emerge, grow the compute control plane: APIs, controllers, scheduling, and integration with Dedalus Machines and our Rust virtual machine monitor. This includes how GPUs are assigned, isolated, exposed to guests and safely reclaimed.
• Work closely with the CTO and founders on architecture decisions. Help hire and mentor engineers as the team grows.
• Choose existing tools where they fit and build only what the product needs. Write tests, deployment workflows, documentation and operating procedures that other engineers can maintain.
• Use AI coding tools to speed up your work. You must be able to explain the design, verify its behavior and diagnose failures yourself.

Logistics: Full-time and on-site in San Francisco. Travel to datacenters is required when deployment and operations call for it. Relocation support is available. Salary is $275,000–$350,000 plus 1.0%–1.5% equity. Meals and office benefits are included.