Compute Engineer, R&D

We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.

We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.

We hire people who care deeply about this problem space. If that is you, please apply!

## How We Operate

- Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done. - Velocity. We drive everything forward as fast as possible. - First principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins. - Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.

## Role Scope

- Qualify next-generation compute: GPUs, servers, and racks tested against the deployment standard before the fleet sees them. - Build and run the benchmark suites: performance, power, and thermals characterized under real workloads. - Break things on purpose: stress, fault injection, and endurance runs that find the weaknesses early. - Write the qualification reports that become fleet standards: configs, firmware, and known issues documented.

## What We're Looking For

The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would .

- You've qualified, validated, or debugged server or GPU systems hands-on. - You benchmark rigorously: reproducible methods, controlled variables, honest numbers. - You've root-caused hardware failures across silicon, firmware, and system levels. - You script your work: automation over checklists. - You've worked with vendors on bugs and gotten fixes shipped.