# Compute Deployment Lead

**Company:** [Fluidstack](https://hotfix.jobs/companies/fluidstack)
**Location:** New York, NY
**Role:** Hardware Engineering
**Salary:** $188k – $253k/yr
**Experience:** 7+ years
**Skills:** gpu clusters, deployment automation, hpc, data center deployment, server deployment, bring-up processes, cluster validation, automation tooling, vendor integration
**Posted:** 2026-07-17

> 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.

## Job Description

## 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.

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**Apply:** https://hotfix.jobs/jobs/5860e51a-3dc5-463d-9452-e87f4548a82d
**Canonical:** https://hotfix.jobs/jobs/5860e51a-3dc5-463d-9452-e87f4548a82d