Researcher, Compute Scaling

Reposted 27 Days Ago
Be an Early Applicant
4 Locations
In-Office
224K-264K Annually
Mid level
Artificial Intelligence • Software
The Role
Build and maintain demand and lead-time forecasts across critical equipment categories, track supplier capacity and delivery risk, model cost/timing trade-offs for large equipment commitments, reconcile supplier/shipment/inventory data into actionable weekly signals, and create forecasting tooling and dashboards to surface disruption ahead of schedule.
Summary Generated by Built In
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. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.

We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.


We hire people who care deeply about this problem space. If that is you, please apply!

How We Operate
  • Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role.

  • Insane urgency. We drive everything forward as fast as possible.

  • Reason from first principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.

  • Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.

  • Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world.

The Supply Chain Team

Examples of key problems the team is working on

  • Supply tens of gigawatts of compute, 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. Our modular build redefines speed in this industry, and it lives or dies on supply chain. Keep procurement permanently off the critical path so schedule compression stays our advantage, not our constraint.

  • 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.

Role Scope
  • Build and maintain the demand and lead-time forecasts that keep procurement ahead of the forward build pipeline across every critical equipment category, from chillers to switchgear to transformers to generators.

  • Track supplier capacity, lead times, and delivery risk across dual-sourced categories, and surface the thresholds that trigger a re-source before the schedule slips.

  • Model the cost and timing trade-offs on multi-hundred-million-dollar equipment commitments so buyers negotiate from data, not guesswork.

  • Turn raw supplier, shipment, and inventory data into the weekly signal the supply chain team runs on, reconciling sources that don't agree.

  • Stand up the forecasting tooling and dashboards that let a lean team see disruption coming instead of reacting to it.

What We're Looking For
  • The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly, tell us where you would.

  • You've built forecasting or planning models that people actually made decisions on, not slideware that got ignored.

  • You've worked with messy operational data from several systems and turned it into a number a team trusted.

  • You catch a lead-time or capacity problem in the data weeks before it becomes a schedule problem.

  • You write analysis clearly enough that a buyer or an executive can act on it without a follow-up meeting.

  • You've partnered with procurement, operations, or finance and shipped analysis that changed what they bought or when.

  • You check your own numbers and you know when a forecast is guessing rather than telling you something.

  • Bonus: Supply chain, procurement, or logistics analytics. Data center or hardware equipment categories. SQL and Python for data work. Statistical or machine-learning forecasting methods. Scaling analysis inside a high-growth operation.

We are committed to pay equity and transparency.

Fluidstack is an Equal Employment Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans’ status, or any other characteristic protected by law. 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. If there is an error with your submission and you did not receive a confirmation email, please email [email protected] with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.

Skills Required

  • Built forecasting or planning models that informed real decisions
  • Worked with messy operational data from multiple systems and produced trusted numbers
  • Identify lead-time or capacity problems before they impact schedule
  • Write clear analysis that enables buyers and executives to act without follow-up
  • Partnered with procurement, operations, or finance and shipped analysis that changed buying or timing
  • Verify own calculations and distinguish when a forecast is uncertain vs. informative
  • Supply chain, procurement, or logistics analytics experience
  • Experience with data center or hardware equipment categories
  • SQL and Python for data work
  • Statistical or machine-learning forecasting methods
  • Experience scaling analysis inside a high-growth operation
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The Company
HQ: London
30 Employees
Year Founded: 2017

What We Do

Instantly reserve dedicated clusters of NVIDIA H200s and GB200s for any scale to supercharge your training and inference workflows.

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