Production Engineer, Compute
Fluidstack · San Francisco, CA
About this role
## About Fluidstack Fluidstack exists to make humanity more free. We build and operate civilization-scale AI compute infrastructure—acquiring power, designing and building data centers, and delivering 10s to 100s of GW faster than anyone else. ## How We Operate - **Be a barrel:** full autonomy, own things end-to-end, take on scope without being asked. - **Insane urgency:** move fast and push forward. - **Reason from first principles:** challenge assumptions; the best idea wins. - **Love of the game:** long hours at high intensity to push the frontier. - **Build something that actually matters:** work that improves the world. ## Production Engineering Team — What You’ll Work On - **Repair pipeline at fleet scale:** automate chip fault detection → triage → RMA → return to service (no human intervention). - **GPU qualification in ~6 months:** burn-in, performance baselining, and NPI execution to define “production-ready” before sites go live. - **Migrate live compute at construction speed:** convert clusters across production sites and make Kubernetes-orchestrated bare metal sustainable at multi-GW annual pace. - **Real-time fleet observability & orchestration:** build the layer that makes hyperscale AI compute operable—debug, tune, and performance-test as the fleet grows. ## Role Scope - **Own compute fleet health end-to-end:** build metrics pipelines, alerting, and a unified health view across Kubernetes-orchestrated workloads and bare metal. - **Turn deployment/repair into a pipeline:** automate compute failures from detection through triage, parts management, and return to service. - **Design and expand the GPU qualification platform:** burn-in, baselining, and NPI execution; define what “good” means before production. - **Own Redfish & BMC tooling:** firmware-level telemetry, fleet-scale log collection, and low-level access for repair/health automation. - **Reliability, scalability, and operations at scale:** aggressive automation, tooling, and incident discipline for one of the largest GPU fleets in the world. ## What We’re Looking For - **5+ years** of applied industry experience. - **Hardware instinct:** comfortable reasoning about failure modes at firmware/silicon level. - **Comfort with ambiguity:** build the map and explain it to others. - **Fast learning:** reach real competence in unfamiliar domains quickly. - **Pager ownership:** run incidents, write postmortems, fix systemic causes, and move on. - **Fluent with AI tooling:** LLM APIs, MCP servers, agentic frameworks; use Claude Code/Cursor (or similar) daily. - **Production automation shipped:** automation other teams depend on; comfortable using AI coding tools in any language. - **Bonus:** hardware lifecycle management & RMA automation; BMC/Redfish/IPMI; GPU qualification/burn-in; workflow/orchestration engines (Temporal/Cadence); metrics/alerting (Prometheus/Grafana); Go or Python. ## Salary & Benefits - Competitive **total compensation** (salary + equity) - Retirement/pension plan (local norms) - Health, dental, and vision insurance - Generous PTO (local norms) - Fluidstack is committed to **pay equity and transparency** ## Equal Employment Opportunity Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration without regard to protected characteristics. ## Apply https://jobs.ashbyhq.com/fluidstack/05c2e69c-42f9-4fcb-9cf0-a467aaf98f1c
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