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FluidStack

Builds and runs GPU clusters for AI labs

Site Reliability Engineer - Compute

Site Reliability EngineeringConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • Treat toil as a problem to eliminate by automating manual repair-workflow steps.
  • Reason about hardware failure modes at the firmware and silicon level, as well as the software stack.
  • Move effectively through ambiguity and explain findings to others.
  • Learn unfamiliar domains quickly.
  • Participate in on-call incident response, write postmortems, and address systemic causes.
  • Use AI tooling, including large language model application programming interfaces, Model Context Protocol servers, agentic frameworks, and tools such as Claude Code or Cursor.
  • Have shipped production automation that other teams depend on and be comfortable working in any programming language using AI coding tools.

Responsibilities

  • Own compute fleet health end to end by building metrics pipelines, alerting, and unified health views across Kubernetes-orchestrated workloads and bare metal.
  • Build and own automation that takes compute failures from detection through triage, parts management, and return to service.
  • Design and expand the GPU qualification platform, including burn-in, performance baselining, and new product introduction execution for each new GPU generation.
  • Own Redfish and baseboard management controller tooling, including firmware-level telemetry, fleet-scale log collection, and low-level access used by repair automation and health tooling.
  • Own the end-to-end reliability, scalability, and operation of the compute fleet at scale.

Desired Qualifications

  • Experience with hardware lifecycle management and return merchandise authorization automation.
  • Experience with baseboard management controller, Redfish, or Intelligent Platform Management Interface tooling.
  • Experience with GPU qualification or burn-in frameworks.
  • Experience with workflow and orchestration engines such as Temporal or Cadence.
  • Experience with metrics and alerting pipelines such as Prometheus and Grafana.
  • Experience with Go or Python.

About the Company

FluidStack

Builds and runs GPU clusters for AI labs

Fluidstack provides large clusters of GPU servers to AI labs training advanced models, and it builds custom data centers for customers that outgrow existing facilities. In 2025, Anthropic chose Fluidstack to build data centers in Texas and New York as part of a $50 billion investment in American AI infrastructure. Labs pay for dedicated clusters of Nvidia GPUs, sometimes tens of thousands of chips, housed in partner data centers around the world. They reach the clusters through a web console or API, while Fluidstack runs the hardware, networking, and day-to-day operations. Fluidstack was founded in London in 2017 and has its headquarters in New York.

Company size
501-1,000
Company stage
Late Stage VC
Total funding
$12.4B
Headquarters
New York City, New York
Founded
2017

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