Compute Engineer, Deployment Team Lead

FluidStack
New York
Workplace: OnsiteFull timeUSD 188,000 - 253,000 annuallyFunction: Administration & Executive AssistanceSkills: ["Extreme ownership","Full autonomy","Velocity","First principles","High-intensity focus"]

Lead compute deployments across multiple data center sites, taking GPU nodes from dock to validated production clusters. Own hall-by-hall deployment schedules for thousands of nodes, and build a scalable bring-up “factory” with automation and crew workflows. Raise and maintain the validation bar so clusters only hand to production after proving performance, with a team operating extreme scale for AI infrastructure.

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FursaFursa
FluidStack
FluidStack
1 month ago

Compute Engineer, Deployment Team Lead

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Source: Company careers pageValidated by: Fursa AI
Last checked: 11 hours agoStatus: Live

Job Summary

Lead compute deployments across multiple data center sites, taking GPU nodes from dock to validated production clusters. Own hall-by-hall deployment schedules for thousands of nodes, and build a scalable bring-up “factory” with automation and crew workflows. Raise and maintain the validation bar so clusters only hand to production after proving performance, with a team operating extreme scale for AI infrastructure.
Location: New York
Workplace: Onsite
Employment Type: Full time
Job Function: Administration & Executive Assistance
Seniority: Manager level

Key Responsibilities

  • •Lead compute deployment across sites, managing the process from dock to validated clusters.
  • •Own the compute deployment schedule per hall, coordinating racking, imaging, burn-in, and validation.
  • •Build the bring-up factory using automation and crew workflows that scale across parallel sites.
  • •Maintain the validation bar so no cluster is handed to production without proving performance.

Pay and Benefits

Salary: USD 188,000 - 253,000 annually
Equity and Bonus:Equity

Key Requirements

  • •Have led compute or server deployment at data center scale.
  • •Have built bring-up processes that significantly cut deployment time.
  • •Have managed mixed teams of engineers and technicians.
  • •Have refused to hand over hardware that didn’t pass, under real pressure.
  • •Bonus experience in GPU clusters, deployment automation, HPC acceptance testing, or vendor integration programs.
Skills:Extreme ownershipFull autonomyVelocityFirst principlesHigh-intensity focus

Company Brief

FluidStack
Builds and deploys large-scale GPU cloud infrastructure for AI labs, enterprises and governments, providing high-performance AI training and inference capacity and rapid data-center deployment services.
Industry: Cloud Computing
Company Size: Medium (51 to 250 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: New York, United States
Founded: 2017
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