Compute Engineer, Deployment Team Lead

Job description

ABOUT FLUIDSTACK 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 DEPLOYMENTS TEAM Examples of key problems the team is working on - Turn empty data halls into serving GPUs in weeks. Deployment owns everything between construction handover and customer-ready compute: racks, fabric, and validation at hundreds of megawatts per site. - Stand up gigawatts a year, hundreds of megawatts at a time. Data halls go from construction handover to serving GPUs in weeks, across multiple sites at once. - Deploy 10s to 100s of GWs with software, not headcount. Bring-up, validation, and handoff run on tooling the team builds, so the hundredth data hall deploys faster than the first instead of needing a hundred times the people. ROLE SCOPE - Lead compute deployment across sites: the team and process taking GPU nodes from dock to validated clusters. - Own the compute deployment schedule per hall: thousands of nodes racked, imaged, burned in, and validated in weeks. - Build the bring-up factory: automation and crew workflows that scale across parallel sites. - Hold the validation bar: no cluster hands to production without proving its performance. - Travel 30-40% of the time to our Data Centers 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 https://jobs.ashbyhq.com/fluidstack/05c2e69c-42f9-4fcb-9cf0-a467aaf98f1c. - You've led compute or server deployment at data center scale. - You've built bring-up processes that cut deployment time by a large factor. - You've managed mixed teams of engineers and technicians. - You've refused to hand over hardware that didn't pass, under real pressure. - Bonus: GPU clusters. Deployment automation. HPC acceptance testing. Vendor integration programs. We are committed to pay equity and transparency. Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law. You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email careers@fluidstack.io with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.