asciimike
Joined 11 years ago
Joined 11 years ago
I'm really excited to see AR take off in use cases like this, given how useful it would be to give all our technicians e.g. a legacy Google Glass (not the Intelligent Eyewear thing) and direct them to a rack, overlay information about a failed component, and walk them through the repair SOP.
Fluidstack is building supercomputers for hyperscalers and frontier labs. We design, construct, and operate gigawatt scale datacenter campuses and then deploy, validate, and operate the GPUs and networking equipment inside.
We're deploying a GW of compute in 2026 in partnership with Anthropic (https://www.anthropic.com/news/anthropic-invests-50-billion-...), and are continuing to scale out capacity in the US.
We're hiring product and engineering across the stack: everything from low level systems programming/firmware on XPUs, automating building controls and datacenter robotics, automating compute and network provisioning and recovery from failures, securing our networks and facilities, and software across dozens of verticals (warehousing, logistics, site selection, commercial operations, talent, legal, etc.)
View hundreds of open roles at fluidstack.io/jobs or send an email to careers at fluidstack dot io
Fluidstack is a full stack AI infrastructure company building datacenters, deploying GPUs, and operating hundreds of thousands of accelerators for top tier AI labs. We're also partnering closely with Anthropic (https://www.anthropic.com/news/anthropic-invests-50-billion-...) on deploying GW scale clusters.
More info at https://careers.fluidstack.io/jobs or ping careers at fluidstack dot io!
Fluidstack is a full stack AI infrastructure company building datacenters, deploying GPUs, and operating hundreds of thousands of accelerators for top tier AI labs. We're also partnering closely with Anthropic (https://www.anthropic.com/news/anthropic-invests-50-billion-...) on deploying GW scale clusters.
More info at https://careers.fluidstack.io/jobs or ping careers at fluidstack dot io!
Less fully featured, but more open (Gaggiuino became closed source post people profiting off the OSS).
I'll also pitch another fun OSS project I sponsored a few years back to build an OSS pressure sensor and 0.1g scale: https://github.com/rhit-coultabm/Consistent-Cups-Espresso-Ac...
Since then it looks like Decent has OSS'ed the DecentScale: https://github.com/decentespresso/openscale
If you go down the "add a pasmo/suica on your phone" then you get into licensing issues with the other cabal (credit card issuers): you need to use an Amex to charge it via Apple Pay (IIRC Visa is now supported, but when I tried it last week my card was declined, so... YMMV).
- Deploying clusters of 1,000+ GPUs and operating them with and for customers.
- Validating correctness and performance of underlying compute, storage, and networking infrastructure, and working with providers to optimize these subsystems.
- Migrating petabytes of data from public cloud platforms to local storage, as quickly and cost effectively as possible.
- Debugging issues anywhere in the stack, from “this server’s fan is blocked by a plastic bag” to “optimizing S3 dataloaders from buckets in different regions”.
- Building internal tooling to decrease deployment time and increase cluster reliability, including automation where the customer benefits clearly outweigh the implementation overhead.
We don't require prior experience with GPUs or AI/ML; we require a willingness to learn quickly, work hard, and obsess about customer success.
Apply here: https://jobs.ashbyhq.com/fluidstack or email careers at fluidstack dot io
> The sudden shift is fueled by fears of tariffs as Donald Trump threatens a trade war that could disrupt the gold market. Traders, worried that gold imports may soon face tariffs, are rushing to get their bullion into the U.S. before the policy takes effect.
Engineers at Fluidstack work on a wide variety of activities, including:
- Deploying clusters of 1,000+ GPUs and operating them with and for customers.
- Validating correctness and performance of underlying compute, storage, and networking infrastructure, and working with providers to optimize these subsystems.
- Migrating petabytes of data from public cloud platforms to local storage, as quickly and cost effectively as possible.
- Debugging issues anywhere in the stack, from “this server’s fan is blocked by a plastic bag” to “optimizing S3 dataloaders from buckets in different regions”.
- Building internal tooling to decrease deployment time and increase cluster reliability, including automation where the customer benefits clearly outweigh the implementation overhead.
We don't require prior experience with GPUs or AI/ML; we require a willingness to learn quickly, work hard, and obsess about customer success.
Apply here: https://jobs.ashbyhq.com/fluidstack or email careers at fluidstack dot io
Fluidstack builds and operates GPU supercomputers for top AI labs, governments, and enterprises. Our customers include Mistral, Poolside, Black Forest Labs, Meta, and more.
Engineers at Fluidstack work on a wide variety of activities, including:
- Deploying clusters of 1,000+ GPUs and operating them with and for customers.
- Validating correctness and performance of underlying compute, storage, and networking infrastructure, and working with providers to optimize these subsystems.
- Migrating petabytes of data from public cloud platforms to local storage, as quickly and cost effectively as possible.
- Debugging issues anywhere in the stack, from “this server’s fan is blocked by a plastic bag” to “optimizing S3 dataloaders from buckets in different regions”.
- Building internal tooling to decrease deployment time and increase cluster reliability, including automation where the customer benefits clearly outweigh the implementation overhead.
We don't require prior experience with GPUs or AI/ML; we require a willingness to learn quickly, work hard, and obsess about customer success.
Apply here: https://jobs.ashbyhq.com/fluidstack/fb45b5dc-614e-40dd-ac5d-... or reach out to mike at fluidstack dot io
1. I believe they require that you have an acquired specific landing page (e.g. crusoe.ai/acquired), which we saw directly as conversions through to our waitlist. The volume was lower than other channels, but the signal was much, much higher.
2. To @scarface_74's comment, "you talk to customer and you can ask them where they heard about you from" is mostly why I made the claim. In particular, when fundraising, basically everyone I talked to said, "I heard about you on Acquired, really interesting business model that I hadn't considered, let's talk more about it."
Sponsorship isn't cheap (I would go so far as to call it expensive), but relative to spending an equivalent amount on search or display ads/billboards on 101/etc., I think it was the right choice at the time.
My only analogy for this is what I call "cruise missile marketing" where you're investing a lot of time/money in building something that is very specifically targeted at high value buyers. It works really well for large, infrequent transactions (raising capital, selling GPU clusters, etc.) and less well for commodity SaaS or B2C products where volume >> everything.