FluidStack

2 weeks ago

Software Engineer, GPU Infrastructure

✓ 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 operate a GPU infrastructure platform that keeps hyperscale AI compute reliable and scalable. Own the compute fleet’s health end to end with metrics pipelines, alerting, and unified observability across Kubernetes-orchestrated workloads and bare metal. Turn deployment and repair into automated pipelines, expand GPU qualification and burn-in workflows, and build low-level Redfish/BMC tooling to support fleet-scale incidents and reliability.

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 by building metrics pipelines, alerting, and a unified health view for every GPU in production.
•Automate compute deployment and repair as pipelines, handling detection through triage and return to service without one-off scripts.
•Design and expand the GPU qualification platform including burn-in, performance baselining, and NPI execution.
•Build and maintain Redfish and BMC tooling for firmware-level telemetry and fleet-scale log collection.
•Drive end-to-end reliability, scalability, and operational excellence for a large at-scale GPU compute fleet.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Equity and Bonus:Equity

Perks:RetirementHealth InsuranceDentalVisionPaid Leave

Key Requirements

•Treat toil as a bug and eliminate manual steps in repair workflows.
•Reason about hardware failure modes at the firmware and silicon level.
•Work effectively in ambiguity by building clarity and explaining it to others.
•Learn rapidly in unfamiliar domains and reach competence quickly.
•Carry a pager, run incidents, write postmortems, and fix systemic root causes.

Experience:AIInfrastructureHardwareAutomation

Skills:Extreme ownershipFirst-principles thinkingVelocityIncident ownershipLearning mindset

Tech Stack:KubernetesBare metalRedfishBMCIPMILLM APIsMCP serversAgentic frameworksClaude CodeCursorTemporalCadencePrometheusGrafanaGoPython

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

Loading job details...

Preparing the role view and application actions.

FluidStack

2 weeks ago

Software Engineer, GPU Infrastructure

✓ 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 by building metrics pipelines, alerting, and a unified health view for every GPU in production.
•Automate compute deployment and repair as pipelines, handling detection through triage and return to service without one-off scripts.
•Design and expand the GPU qualification platform including burn-in, performance baselining, and NPI execution.
•Build and maintain Redfish and BMC tooling for firmware-level telemetry and fleet-scale log collection.
•Drive end-to-end reliability, scalability, and operational excellence for a large at-scale GPU compute fleet.

Pay and Benefits

Salary: USD 175,000 - 300,000 annually

Equity and Bonus:Equity

Perks:RetirementHealth InsuranceDentalVisionPaid Leave

Key Requirements

•Treat toil as a bug and eliminate manual steps in repair workflows.
•Reason about hardware failure modes at the firmware and silicon level.
•Work effectively in ambiguity by building clarity and explaining it to others.
•Learn rapidly in unfamiliar domains and reach competence quickly.
•Carry a pager, run incidents, write postmortems, and fix systemic root causes.

Experience:AIInfrastructureHardwareAutomation

Skills:Extreme ownershipFirst-principles thinkingVelocityIncident ownershipLearning mindset

Tech Stack:KubernetesBare metalRedfishBMCIPMILLM APIsMCP serversAgentic frameworksClaude CodeCursorTemporalCadencePrometheusGrafanaGoPython

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