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Fluidstack

200 open roles · Acceleration

Machine Learning Engineer

Full-time
$224k to $344k USD / year
Posted 2 months ago
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Where you can work

On-site

4 workplaces

  • Austin, Texas, United States
  • New York City, New York, United States
  • California, United States
  • Seattle, Washington, United States
View location wording from the posting
  • Austin, Texas, United States
  • New York, NY, United States
  • San Francsisco, California, US
  • Seattle, Washington, United States

Employer description

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.

Role Scope

  • Build ML and LLM systems that run inside the company's operations: forecasting build timelines, flagging schedule risk, and extracting structure from vendor documents.
  • Own models end to end, from problem framing and data through deployment, evaluation, and iteration in production.
  • Ship agentic systems with real guardrails, authorization, audit, and evals, so agents act on company systems instead of just advising.
  • Partner with data engineering and product pods to put predictions in the tools people already use.

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 shipped ML or LLM features to production and owned them after launch.
  • You've built evaluation harnesses that told you the truth about model quality before users did.
  • You reach for the simplest model that works and can defend the choice.
  • You've worked hands-on with LLM APIs, fine-tuning, or retrieval systems on real business problems.
  • You write production-quality code and work fluently with AI coding tools.
  • Bonus: Forecasting or scheduling problems. Document extraction at scale. Agentic frameworks and MCP. Temporal or workflow engines.

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 careers@fluidstack.io 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.

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