Fluidstack

Fluidstack

Site Operations Capacity Analyst

Austin, TX

Sponsorship not specified$10k-$100kDetected 1 day ago
PythonSQLData VisualizationComputer VisionSupply ChainProcurementPower Electronics

About the role

  • ABOUT FLUIDSTACK We exist to make humanity more free.
  • For most of human history, you farmed or you starved.
  • Technology gave people more time for the things they wanted to do, instead of things they had to do.

Responsibilities

  • Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
  • Velocity. We drive everything forward as fast as possible.
  • Supply compute at a scale of 10s to 100s of GWs, the largest build out of compute in history. Qualify and dual-source across every critical equipment category, with lead-time and capacity thresholds tied directly to the forward build pipeline.
  • Make supply chain the reason we build faster than anyone.
  • Build the most accurate supply chain prediction modelling that exists. Use the frontier of AI to forecast lead times, demand, and disruption with a precision the industry has never had, and turn that foresight into a structural edge.
  • Build the reporting that connects deployment schedules to sellable capacity for commercial and leadership.

Nice to have

  • Data center capacity planning.
  • Power systems knowledge.
  • BI tooling (Tableau, Looker, Hex).
  • Cloud capacity or fleet economics.
  • Fluidstack is an Equal Employment Opportunity Employer.
  • Fluidstack will consider for employment qualified applicants with arrest and conviction records pursuant to applicable law.
  • You will receive a confirmation email once your application has successfully been accepted.

Compensation

  • $10k-$100k

Benefits

  • We are committed to pay equity and transparency.

Company info

  • Our modular build redefines speed in this industry, and it lives or dies on supply chain.

This listing is sourced directly from Fluidstack's careers page and normalized into a canonical job model.