GPU Infrastructure Engineer

Senior EngineerA profitable, high growth technology company in the Bay Area is expanding the team that powers the compute behind its most important research and products. As a senior engineer, you will write production code that decides how large fleets of accelerators are scheduled, served and repaired. You will become the engineer researchers call when a critical run has to go right, with real ownership and visible impact from day one.What you will do:Build and operate GPU clusters across public cloud, specialty GPU providers and owned data centersDesign schedulers and automation that increase utilization and recover from hardware failures without manual interventionStand up fast model serving and distributed training environmentsReport on where compute spend goes and where it can be reducedWhat you bring:5+ years engineering production distributed systems or ML infrastructureStrong Python plus Go or C++Deep Kubernetes experience, with exposure to Slurm or similar schedulersProven experience running large GPU workloads on a modern training or serving stackWillingness to carry the pager for systems that other teams depend on