Reliability Engineer, R&D

Reposted 22 Days Ago
Be an Early Applicant
4 Locations
In-Office
169K-208K Annually
Mid level
Artificial Intelligence • Software
The Role
Lead reliability engineering for a reference design: build and validate availability and RAM models, run cross-discipline FMEAs, quantify failure rates and redundancy trade-offs, and close the loop by feeding fleet field-failure data back into designs to improve maintainability and uptime.
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.

Role Scope
  • Own reliability engineering for the reference design: availability modeled, weak points found, and fixes engineered before deployment.

  • Build the RAM models: failure rates, redundancy, and maintainability quantified per configuration.

  • Run FMEAs across disciplines: failure modes cataloged and designed out with the engineering teams.

  • Close the loop with the fleet: field failures fed back into models and design changes.

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 done reliability engineering for infrastructure, energy, or complex hardware.

  • You've built availability models decision-makers used.

  • You've led cross-discipline FMEAs that changed designs.

  • You mine field data for the truth about failure rates.

  • You argue redundancy trade-offs in dollars and nines.

  • Bonus: Data center topologies. RAM modeling software. Weibull analysis. Maintenance strategy design.

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

  • Experience in reliability engineering for infrastructure, energy, or complex hardware.
  • Built availability/RAM models used by decision-makers.
  • Led cross-discipline FMEAs that influenced design changes.
  • Experience mining and analyzing field failure data to determine failure rates.
  • Ability to evaluate redundancy trade-offs in cost and availability (dollars and nines).
  • Familiarity with data center topologies.
  • Experience with RAM modeling software.
  • Weibull analysis and maintenance strategy design experience.
Am I A Good Fit?
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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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