Compute Engineer, Deployment

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.

Examples of key problems the team is working on

• Bring gigawatts of accelerators from first power-on to production. Facility availability to ready-for-service across thousands of racks per site, with a new data hall landing every few weeks.
• Make rack qualification faster than the fleet grows. Firmware baselines, burn-in, and cluster validation proven on every rack before a customer workload touches it, at a pace that never becomes the critical path.
• Scale by tooling, not headcount. Deployed megawatts grow severalfold next year while the team stays near-flat, because anything done twice by hand becomes software.

Role Scope

• Own compute turn-up from facility availability to ready-for-service: the stretch after the network hands off and before customers run workloads.
• Qualify racks at scale: establish firmware baselines, configure BMC and BIOS, run burn-in, and validate at node and cluster level across hundreds of racks per site on GPU and custom accelerator platforms.
• Drive qualification through the base-management Kubernetes platform and provisioning stack (discovery, imaging, firmware updates, shared services), burning down qual queues with tooling rather than manual runs.
• Triage hardware failures found in qualification: isolate to component, drive RMA and vendor escalation, and feed failure patterns back into the qual gates.
• Run turn-up remotely by default, with on-site pulses of roughly a week per data hall as new halls reach facility availability, plus occasional overlapping-site weeks.
• Partner with network deployment, ICT, data center operations, and hardware teams during turn-up windows, and support incident response on freshly-live capacity.
• Ability to travel 30-40% of the time to our Data Centers and Labs, as needed.

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 brought up server or GPU fleets at scale, hundreds of nodes or more, and taken them all the way to production.
• You work deep in Linux and out-of-band management: BMC, IPMI, and Redfish are daily tools for you, not occasional lookups.
• You've automated hardware workflows in Python or Go rather than clicking through them, and the second time you do anything by hand you turn it into software.
• You've worked physically in data halls, racking, cabling, and swapping components, and you're just as effective acting as remote hands or directing them.
• You triage failures methodically across hardware, firmware, and software, isolating the fault to a component before reaching for a fix.
• You travel for turn-up windows when a new data hall comes online.
• Bonus: Kubernetes-based bare-metal provisioning. Accelerator platform bringup (NVIDIA, AMD, or custom). Burn-in and stress harness design. DCIM and inventory tooling.

We are committed to pay equity and transparency.

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 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.