FluidStack

1 month ago

Production Engineer, Compute

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Own and scale the compute fleet for Fluidstack’s AI-grade infrastructure. Build end-to-end health metrics, automate failure repair pipelines, and design the XPU qualification platform for new GPU/TPU generations. Drive fleet reliability and performance across Kubernetes and bare metal at hyperscale, with a focus on low-latency incident response and tooling.

Location: San Francisco, New York, Seattle, Austin

Workplace: Hybrid

Employment Type: Full time

Job Function: Manufacturing & Production Operations

Key Responsibilities

•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 and TPU in production — across Kubernetes-orchestrated workloads and bare metal, at scale.
•Turn 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 XPU qualification platform. Burn-in, performance baselining, and NPI execution for every new GPU and TPU 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 XPU fleets in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionPensionPaid Leave

Key Requirements

•Shipped production automation or tooling at scale in a hardware/software environment
•Experience designing or operating compute infrastructure (GPU/TPU, Kubernetes, bare metal)
•Proficiency with telemetry, metrics, and incident response tooling (e.g., Redfish, BMC, Prometheus, Grafana)
•Ability to own complex end-to-end systems and drive projects with minimal supervision
•Comfort with ambiguity, rapid iteration, and working across hardware and software teams

Experience:HyperscaleAi hardwareCompute infrastructure

Skills:KubernetesGoPythonPrometheusGrafanaRedfishIPMIGPUTPUTemporalCadence

Languages:English

Tech Stack:KubernetesPrometheusGrafanaRedfishIPMIGPUTPUGoPythonTemporalCadence

Company Brief

FluidStack

Builds and deploys large-scale GPU cloud infrastructure for AI labs, enterprises and governments, providing high-performance AI training and inference capacity and rapid data-center deployment services.

Industry: Cloud Computing

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: New York, United States

Founded: 2017

Glassdoor: 4.7

Website LinkedIn Glassdoor

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FluidStack

1 month ago

Production Engineer, Compute

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Location: San Francisco, New York, Seattle, Austin

Workplace: Hybrid

Employment Type: Full time

Job Function: Manufacturing & Production Operations

Key Responsibilities

•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 and TPU in production — across Kubernetes-orchestrated workloads and bare metal, at scale.
•Turn 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 XPU qualification platform. Burn-in, performance baselining, and NPI execution for every new GPU and TPU 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 XPU fleets in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionPensionPaid Leave

Key Requirements

•Shipped production automation or tooling at scale in a hardware/software environment
•Experience designing or operating compute infrastructure (GPU/TPU, Kubernetes, bare metal)
•Proficiency with telemetry, metrics, and incident response tooling (e.g., Redfish, BMC, Prometheus, Grafana)
•Ability to own complex end-to-end systems and drive projects with minimal supervision
•Comfort with ambiguity, rapid iteration, and working across hardware and software teams

Experience:HyperscaleAi hardwareCompute infrastructure

Skills:KubernetesGoPythonPrometheusGrafanaRedfishIPMIGPUTPUTemporalCadence

Languages:English

Tech Stack:KubernetesPrometheusGrafanaRedfishIPMIGPUTPUGoPythonTemporalCadence

Company Brief

FluidStack

Industry: Cloud Computing

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Funding: Series A

Headquarters: New York, United States

Founded: 2017

Glassdoor: 4.7

Website LinkedIn Glassdoor