Software Engineer, Compute; GPU

Fluidstack Production Engineering Team

Examples of key exciting problems the team is working on:

• Build the repair pipeline that keeps pace with a 10 GW fleet: at our scale, a GPU failure isn't a ticket. It's a throughput problem. We're building the automation that takes a chip from fault detection through triage, RMA, and return to service without human intervention.
• Qualify every new GPU generation inside a 6-month build window: our platform covers burn-in, performance baselining, and NPI execution. It has to define "production-ready" before a site goes live, not after. New hardware gets certified at speeds unheard of in the industry.
• Migrate live compute at construction speed: we're converting clusters across production sites simultaneously, bringing new sites online, and making Kubernetes-orchestrated bare metal sustainable at the pace we're building – multiple GW annually.
• See and own the entire fleet in real time, at any scale: build the observability and orchestration layer that makes hyperscale AI compute actually operable. Debug, tune, and performance-test infrastructure that grows by another site every few months.

• Own compute fleet health end to end. Build the metrics pipelines, alerting, and unified health view that tell you the true state of every GPU in production — across Kubernetes-orchestrated workloads and bare metal, at scale.
• Turn deployment/repair into a pipeline, not a procedure. Build and own the automation that takes a compute failure from detection through triage, parts management, and return to service. No one-off scripts, no heroics.
• Design and expand the GPU qualification platform. Burn-in, performance baselining, and NPI execution for every new GPU generation. You define what "good" looks like before hardware goes into production.
• Own Redfish and BMC tooling. Firmware-level telemetry, log collection at fleet scale, and the low-level access layer that repair automation and health tooling depend on.
• Own end-to-end reliability, scalability, and operation of the compute fleet at-scale. Fluidstack is building one of the largest GPU fleets in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.

• Competitive total compensation package (salary + equity).
• Retirement or pension plan, in line with local norms.
• Health, dental, and vision insurance.
• Generous PTO policy, in line with local norms.

The base salary range for this position is $175,000 - $300,000 per year, depending on experience, skills, qualifications, and location. This range represents our good faith estimate of the compensation for this role at the time of posting. Total compensation may also include equity in the form of stock options.

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.