Qualification Engineer, Labs

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!

• 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.

• 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.

Examples of key problems the team is working on

• Qualify the hardware the frontier runs on before it runs anywhere else. First samples of next-generation accelerators, switches, storage, and liquid cooling land here, and leave as production-ready platforms with runbooks the whole fleet inherits.

• Compress silicon-to-production to weeks. The lab closes the gap between vendor sample and customer-ready gigawatt infrastructure, and every week cut here pulls the entire 10 GW deployment curve forward.

• Run the lab like a production site. Provisioning, telemetry, demand management, and liquid cooling mirror production architecture exactly, so a qualification pass in the lab is a deployment guarantee in the field.

• Prove the power envelope nobody else will touch. Dynamic demand management lets AI compute deploy beyond nominal electrical capacity, and the lab validates the full detection-to-shutdown response chain that makes it safe.

• Bring up first-sample accelerator platforms (NVIDIA, AMD, custom accelerators) end to end: rack integration, liquid cooling commissioning, firmware baseline establishment, network connectivity, and software stack validation at rack densities up to and beyond 120 kW.

• Validate network platforms across Broadcom Tomahawk, Broadcom Jericho, and NVIDIA Spectrum silicon, driving Keysight Ixia traffic generation for RFC 2544/2889 benchmarking, line-rate stress, and protocol correctness.

• Verify the optical layer with EXFO test equipment, covering BER characterization and power budget analysis across the link inventory a qualification depends on.

• Qualify CDUs and liquid cooling across nVent, CoolIT, and Vertiv platforms: commissioning procedures, BMS telemetry integration, leak detection validation, coolant chemistry verification, and the operational runbooks that fall out of each pass.

• Exercise the full power over subscription response chain: graceful and forced shutdown paths, power-cap and p-state levers via BMC, ATS transfer scenarios, breaker-trip detection, rPDU commissioning with outlet-level telemetry, and repeatable power-virus stress harnesses against accelerator hardware.

• Co-develop qualification matrices with hardware partners, evaluate converged local-NVMe storage platforms (Weka, Hammerspace, VAST Data), and turn results into runbooks production teams inherit.

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 personally brought up servers, accelerators, or switches from first power-on: racking, cabling, firmware, first boot, and everything that goes wrong in between.

• You script your test harnesses and automation rather than clicking…