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.
THE COMPUTE PRODUCTION TEAM
The Compute Production team builds the data foundations and internal products that let Fluidstack bring gigawatt-scale AI compute online and keep it running.
Examples of key problems the team is working on:
- Build the ontology that models compute production end to end, from hardware and networks to the operational workflows that deliver clusters to customers
- Turn fragmented operational data spread across tools, spreadsheets, and people's heads into a single source of truth engineers and operators can build against
- Ship product surfaces that give compute production teams real leverage: fewer manual handoffs, faster diagnosis, clearer state of the fleet
- Apply LLM-era tooling to operational workflows where structured data and automation can replace repetitive human effort
ROLE SCOPE
- Own product direction for the team's ontology and data products serving compute production: the roadmap, the priorities, and the success metrics that justify them
- Turn messy compute production domains into data models, specs, and product surfaces clear enough that engineers can ship against them without a second round of discovery
- Drive technical tradeoffs with engineers and ship end to end, from problem definition through delivery
- Run direct discovery with compute production stakeholders to understand their domain, then validate that what you built actually changes how they work