1,803,103open jobs
104,022companies
272,052added this week
Browse all
Salary
$208k – $269k per year
Location
In office (San Francisco, New York, Seattle, Austin)
Visa
H-1B filings in 12 months: 23 · for this role: 10
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Jul 20, 2026. Fluidstack scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Fluidstack is an artificial intelligence infrastructure company that builds and operates large GPU clusters for model developers, research labs and enterprises. It began by aggregating idle compute from data centres and has since moved into developing dedicated gigawatt-scale sites, arranging the power, financing and construction alongside the clusters themselves, and it works with national governments and sovereign programmes as well as commercial labs. The company is headquartered in New York with a substantial London presence, and it competes with the specialist GPU cloud providers by taking on the energy and site development problem rather than only reselling capacity.

About Fluidstack

We exist to make humanity more free. For most of human history, you farmed or you starved. Technology gave people more time for the things they wanted to do, instead of things they had to do. Powerful AI will be the biggest lever for human choice we've ever built - but only if models are aligned with what humanity actually wants. There are groups building AI who don't share these goals. Whoever deploys frontier compute infrastructure fastest will decide whether AI expands human freedom or shrinks it.

We're singularly focused on delivering 10 to 100s of GWs of compute faster than anyone else, rethinking every layer of the stack. We acquire power, design and build data centers, and operate them - with teams spanning hardware and software. Speed and scale are our key differentiators. Come be a part of building civilization-scale infrastructure for AI.

We hire people who care deeply about this problem space. If that is you, please apply!

How We Operate

  • Be a barrel. Full autonomy. Own things end to end, take on scope without being asked, no permission required to operate outside your core role.

  • Insane urgency. We drive everything forward as fast as possible.

  • Reason from first principles. Challenge every assumption. Zero analogy thinking, no egos, the best idea wins.

  • Love of the game. The frontier of AI is the most interesting problem of our time. We put in long hours at high intensity to push the frontier forward.

  • Build something that actually matters. If you're going to spend your time, spend it on something that matters to the world.

The Production Engineering Team

Examples of key exciting problems the team is working on

  • Build the repair pipeline that keeps pace with a fleet of 10s to 100s of GWs: 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.

Role Scope

  • 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.

What We're Looking For

The below is a starting point. We always make space for exceptional people, so if you don't fit this role exactly,tell us where you would.

  • You treat toil as a bug. Manual steps in a repair workflow are a backlog item, not a job description.

  • You have an instinct for hardware. You're comfortable reasoning about failure modes at the firmware and silicon level, not just the software stack above it.

  • You move toward ambiguity, not away from it. You walk into the fog, build the map, and explain it to everyone else.

  • You learn at a steep slope. You reach real competence in an unfamiliar domain fast. We value this over existing expertise.

  • You carry a pager without flinching. You run the incident, write the postmortem, fix the systemic cause, and move on.

  • You're fluent with AI tooling. LLM APIs, MCP servers, and agentic frameworks, and you drive Claude Code, Cursor, or similar every day.

  • You've shipped production automation that other teams depend on, and you're comfortable in any language using AI coding tools.

  • Bonus: Hardware lifecycle management and RMA automation. BMC/Redfish or IPMI tooling. GPU qualification or burn-in frameworks. Workflow and orchestration engines (Temporal, Cadence). Metrics and alerting pipelines (Prometheus, Grafana). Go or Python...

Salary & Benefits

  • 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.

Total compensation may also include equity in the form of restricted stock units.

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.

You will receive a confirmation email once your application has successfully been accepted. If there is an error with your submission and you did not receive a confirmation email, please email [email protected] with your resume/CV, the role you've applied for, and the date you submitted your application-- someone from our recruiting team will be in touch.

Free account
Stop reading job ads. Get the ones that fit.
One free account turns this page into a shortlist built around your stack, your level and your pay.
Match on every job. Stack, seniority, pay and location, scored against your profile.
1,803,103 open roles. Read straight off company career pages, refreshed every day.
Unlimited applications. Every one you send is tracked in one place, on-site or on a company board.
3 tailored CVs a month. Rewritten for the exact job you are applying to. Included free.
Create a free account Continue with Google
Free forever. No card. Under a minute.

Your match

How well do you fit this role?
Two answers are enough for a real match. No account needed.
Check my fit
Answers stay in this browser until you create an account.

Recommended for you based on this role

DevOps
Similar stack
Same company
San Francisco
≈ $95k – $184k per year (Estimated) • In office • 6+ years exp • Plano
Python
Databases
PostgreSQL
DynamoDB
ElasticSearch
OpenSearch
DevOps
Terraform
GitHub Actions
AWS CDK
CloudFormation
Dynatrace
CI/CD
Jenkins
AWS
Docker
Kubernetes
Amazon EKS
AWS Lambda
Amazon S3
IAM
Amazon ECS
Amazon CloudWatch
AWS Step Functions
API Gateway
Cybersecurity
Okta
SonarQube
Least Privilege
Apply
$129k – $175k per year • Equity • In office • Full-Time • 5+ years exp • Bachelor's Degree • North Reading
Apply
$151k – $205k per year • Equity • In office • Full-Time • 8+ years exp • Bachelor's Degree • North Reading
Robotics
Sensor Fusion
Apply
$149k – $201k per year • Equity • In office • Full-Time • 10+ years exp • Bachelor's Degree • Austin
Apply
$129k – $175k per year • Equity • In office • Full-Time • Seattle
Python
Go
Java
Rust
Ruby
C#
C++
DevOps
CI/CD
AWS
Linux
Unix
Apply
≈ $54k – $136k per year (Estimated) • Hybrid • Full-Time • Auckland
Python
TypeScript
AI/ML
Model Context Protocol
AI Agents
LLM
RAG
LLM Guardrails
DevOps
Platform Engineering
Management
Agile
Apply
Product Analyst 3 days ago
≈ $17k – $39k per year (Estimated) • Remote (EAEU) • Full-Time • Moscow
Python
SQL
Apply
Data Scientist 15 days ago
≈ $13k – $34k per year (Estimated) • In office • 3+ years exp • Bachelor's Degree • Minsk
Python
SQL
AI/ML
CatBoost
Scikit-learn
NumPy
Machine Learning
DevOps
Git
Apply
In office • Full-Time • Moscow
Python
SQL
Python
pySpark
Databases
ClickHouse
Greenplum
Vertica
AI/ML
Polars
Hadoop
CatBoost
Spark
Airflow
Dagster
XGBoost
Scikit-learn
Computer Vision
NLP
LightGBM
TensorFlow
Pandas
NumPy
PyTorch
LLM
RAG
Machine Learning
DevOps
GCP
Yandex Cloud
Azure
AWS
Docker
Kubernetes
Analytics
Tableau
Power BI
Apply
≈ $43k – $96k per year (Estimated) • In office • 4+ years exp • Cairns
Python
PowerShell
DevOps
VMWare
Azure
Windows
TCP/IP
DNS
DHCP
Cybersecurity
Active Directory
Management
Confluence
Jira
ITIL
Apply
$155k – $199k per year • In office • Full-Time • Austin • New York • San Francisco • Seattle
DevOps
HPC
Apply
$208k – $263k per year • In office • Full-Time • Austin • New York • San Francisco • Seattle • Los Angeles
DevOps
AWS
Apply
$208k – $263k per year • In office • Full-Time • Austin • New York • San Francisco • Seattle • Los Angeles
Apply
$173k – $279k per year • In office • Full-Time • San Francisco • New York • Seattle • Austin • London
Python
AI/ML
Cursor
Claude Code
DevOps
gRPC
BGP
Apply
$224k – $300k per year • In office • Full-Time • San Francisco • New York • Seattle • Austin
Python
TypeScript
AI/ML
Cursor
Claude Code
Model Context Protocol
Computer Vision
AI Agents
LLM
OpenAI
Anthropic
Knowledge Graph
Apply
$130k – $200k per year • In office • 3+ years exp • New York • Houston • San Francisco • Seattle
Python
AI/ML
InfiniBand
DevOps
Kubernetes
HPC
Linux
Apply
$75k – $180k per year • In office • 7+ years exp • Los Angeles • San Francisco
Python
SQL
Databases
MySQL
PostgreSQL
Firestore
Google BigQuery
BigQuery
AI/ML
AI Agents
DevOps
Terraform
GCP
Prometheus
Docker
Kubernetes
SRE
Platform Engineering
Google GKE
Apply
≈ $134k – $248k per year (Estimated) • Equity • Remote (United States) • Full-Time • 10+ years exp • Master's Degree • San Francisco
AI/ML
TensorFlow
Triton
TorchServe
Feature Store
Machine Learning
DevOps
GCP
Platform Engineering
Apply
$131k – $145k per year • Equity • Hybrid • 4+ years exp • Bachelor's Degree • San Francisco
SQL
Apply
≈ $146k – $277k per year (Estimated) • In office • 5+ years exp • Houston • New York • San Francisco • Seattle
Python
AI/ML
Edge AI
DevOps
Prometheus
Grafana
Linux
BGP
OSPF
Apply
See all jobs
This is one of many
1,803,103 more open roles from verified company boards, updated every day.