
Job Overview
Location
San Francisco, CA
Job Type
Full-time
Category
Engineering
Date Posted
July 21, 2026
Full Job Description
đź“‹ Description
- • 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!
- • Extreme ownership. Full autonomy. Own things end to end often taking on scope outside your core role without being asked to get things done.
- • Velocity. We drive everything forward as fast as possible.
- • 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.
- • Examples of key exciting problems the team is working on
- • Turn every network fault from a mystery into a closed ticket: link diagnostics across router-router and NIC-to-router paths, remote command execution across the fleet, and repair visualization that shows exactly what's broken and why. At this scale, debugging has to be systematic, not artisanal.
- • Build the network repair pipeline that runs itself: from automated fault detection through RMA initiation, ticket integration, transceiver lifecycle tracking, and return to service, across DC fabric, edge, and host-to-network layers. When a new site comes online every six months, manual repair doesn't keep up.
- • Build the network monitoring platform for a fleet that never stops growing: define requirements, alerting lifecycle, and health dashboards from scratch, for infrastructure spanning multiple hyperscale sites today and 10s to 100s of GWs ahead. It doesn't exist yet. We're building it.
- • Own network fleet health end to end. Define the realtime monitoring requirements, build the alerting lifecycle, and ship the dashboards that give every on-call engineer a true picture of network state across all sites.
- • Build active debugging tooling. Link diagnostics, remote command execution across the fleet, and repair visualization — the tools that turn a network fault from a mystery into a solvable problem, fast.
- • Turn repair into a pipeline, not a procedure. Build the automation that takes a network failure from detection through parts management and return to service. Ticket integration, repair lifecycle pipelines, transceiver and optics tracking — owned, not improvised.
- • Own network qualification and validation. Build the frameworks that gate new sites and hardware into production. You define what a healthy network looks like before it carries traffic.
- • Own end-to-end reliability, scalability, and operation of the network at-scale. Fluidstack is building one of the largest datacenter networks in the world and that can only be accomplished with aggressive automation, tooling, and incident discipline.
- • 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. https://jobs.ashbyhq.com/fluidstack/05c2e69c-42f9-4fcb-9cf0-a467aaf98f1c
Skills & Technologies
See exactly how your profile matches this role — strengths, skill gaps, and what to do about them.
About FluidStack Inc.
FluidStack Inc. operates a distributed cloud platform that aggregates under-utilized GPUs in data centers and individual machines worldwide, renting them on-demand to AI researchers, startups, and enterprises for training and inference workloads. The company automates deployment, security, and billing, offering prices up to 80% below traditional hyperscalers while providing instant access to high-end NVIDIA A100, H100, and consumer GPUs through a single API and web console. Headquartered in London, FluidStack targets machine-learning engineers who need scalable, low-cost compute without long-term commitments, claiming thousands of active nodes and customers including Fortune 500 enterprises and leading research labs.
Subscribe to the weekly newsletter for similar remote roles and curated hiring updates.
Newsletter
Weekly remote jobs and featured talent.
No spam. Only curated remote roles and product updates. You can unsubscribe anytime.
Similar Opportunities

NETGEAR, Inc.
8 days ago

Unilever PLC
19 days ago

Silver.com LLC
10 days ago

Latamcent
2 months ago