FluidStack

2 weeks ago

Software Engineer, Compute (GPU)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Build and automate GPU compute fleet operations end to end for hyperscale AI infrastructure. Own compute fleet health with metrics pipelines, alerting, and unified observability across Kubernetes-orchestrated workloads and bare metal. Turn deployment and repairs into reliable pipelines, design the GPU qualification/burn-in platform, and build Redfish/BMC tooling to support firmware-level telemetry. Drive incident discipline and scalable reliability as the fleet grows.

Location: San Francisco, New York, Austin, Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Own compute fleet health end to end, including metrics pipelines, alerting, and unified health views.
•Turn deployment and repair into pipelines (not one-off scripts), from detection through triage and return to service.
•Design and expand the GPU qualification platform, including burn-in, performance baselining, and NPI execution.
•Own Redfish and BMC tooling for firmware-level telemetry and fleet-scale log collection.
•Drive end-to-end reliability, scalability, and operational discipline for the at-scale compute fleet.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionRetirementPaid Leave

Key Requirements

•Treat toil as a bug and replace manual steps in repair workflows with automation.
•Reason about hardware failure modes at the firmware and silicon level.
•Move toward ambiguity by building a map and explaining it clearly to others.
•Learn quickly in unfamiliar domains and reach real competence fast.
•Run incidents reliably: carry a pager, lead response, write postmortems, and fix systemic causes.

Experience:AIInfrastructureProduction automationHardwareKubernetes

Skills:Extreme ownershipAutonomyVelocityFirst-principles thinkingIncident management

Tech Stack:KubernetesRedfishBMCIPMILLM APIsMCP serversAgentic frameworksClaude CodeCursorTemporalCadencePrometheusGrafanaGoPythonRMA

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

2 weeks ago

Software Engineer, Compute (GPU)

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: San Francisco, New York, Austin, Seattle

Workplace: Onsite

Employment Type: Full time

Job Function: Software Engineering

Key Responsibilities

•Own compute fleet health end to end, including metrics pipelines, alerting, and unified health views.
•Turn deployment and repair into pipelines (not one-off scripts), from detection through triage and return to service.
•Design and expand the GPU qualification platform, including burn-in, performance baselining, and NPI execution.
•Own Redfish and BMC tooling for firmware-level telemetry and fleet-scale log collection.
•Drive end-to-end reliability, scalability, and operational discipline for the at-scale compute fleet.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Equity and Bonus:Equity

Perks:Health InsuranceDentalVisionRetirementPaid Leave

Key Requirements

•Treat toil as a bug and replace manual steps in repair workflows with automation.
•Reason about hardware failure modes at the firmware and silicon level.
•Move toward ambiguity by building a map and explaining it clearly to others.
•Learn quickly in unfamiliar domains and reach real competence fast.
•Run incidents reliably: carry a pager, lead response, write postmortems, and fix systemic causes.

Experience:AIInfrastructureProduction automationHardwareKubernetes

Skills:Extreme ownershipAutonomyVelocityFirst-principles thinkingIncident management

Tech Stack:KubernetesRedfishBMCIPMILLM APIsMCP serversAgentic frameworksClaude CodeCursorTemporalCadencePrometheusGrafanaGoPythonRMA

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