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FluidstackFluidstack

Compute Deployment Lead

Lead the end-to-end compute deployment process for large-scale GPU clusters at data centers, owning schedules, building scalable automation and workflows, managing mixed engineering/technician teams, and enforcing strict validation standards to rapidly turn over halls into production compute.

About the job

Lead Compute Deployment

Responsibilities

  • 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.
  • 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 10GW 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.

Requirements

  • Led compute or server deployment at data center scale.
  • Built bring-up processes that cut deployment time by a large factor.
  • Managed mixed teams of engineers and technicians.
  • Refused to hand over hardware that didn't pass, under real pressure.

Nice-to-Haves

  • GPU clusters.
  • Deployment automation.
  • HPC acceptance testing.
  • Vendor integration programs.

Skills

Gpu Clusters, Deployment Automation, Hpc, Data Center Deployment, Server Deployment, Bring-Up Processes, Cluster Validation, Automation Tooling, Vendor Integration

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