Production Engineer, Compute

Production Engineer, Compute LocationSan Francisco, CA; Austin, TX; New York, NY; Seattle, WAEmployment TypeFull timeLocation TypeHybridDepartmentOperationsCompensation$208K – $269KTo provide greater transparency to candidates, we share base pay ranges for all US-based job postings. Our compensation package includes base salary, equity for all full time roles, benefits, and, for applicable roles, commissions plans.This range reflects a good-faith estimate based on the applicable pay scale, the range previously established for this role, the compensation of individuals currently in equivalent positions, and/or the budgeted amount for the position. Actual compensation may vary based on experience, qualifications, and other factors.We welcome compensation discussions if this range doesn't meet your requirements. Outstanding candidates may be eligible for adjusted terms, plus meaningful equity that ensures you benefit directly from the company's long-term performance.Total compensation may also include equity in the form of restricted stock units. About FluidstackWe 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 OperateExtreme 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 Production Engineering TeamExamples of key exciting problems the team is working onBuild the repair pipeline that keeps pace with a fleet of 10s to 100s of GWs: at our scale, a GPU failure isn't a ticket. It's a throughput problem. We're building the automation that takes a chip from fault detection through triage, RMA, and return to service without human intervention.Qualify every new GPU generation inside a 6-month build window: our platform covers burn-in, performance baselining, and NPI execution. It has to define "production-ready" before a site goes live, not after. New hardware gets certified at speeds unheard of in the industry.Migrate live compute at construction speed: we're converting clusters across production sites simultaneously, bringing new sites online, and making Kubernetes-orchestrated bare metal sustainable at the pace we're building – multiple GW annually.See and own the entire fleet in real time, at any scale: build the observability and orchestration layer that makes hyperscale AI compute actually operable. Debug, tune, and performance-test infrastructure that grows by another site every few months.Role ScopeOwn compute fleet health end to end. Build the metrics pipelines, alerting, and unified health view that tell you the true state of every GPU in production — across Kubernetes-orchestrated workloads and bare metal, at scale.Turn deployment/repair into a pipeline, not a procedure. Build and own the automation that takes a compute failure from detection through...