Job Description

About Fluidstack Fluidstack is building GPU supercomputers for top AI labs, governments, and enterprises. Our customers include Mistral, Poolside, Black Forest Labs, Meta, and more. Our team is small, highly motivated, and focused on providing a world class supercomputing experience. We put out customers first in everything we do, working hard to not just win the sale, but to win repeated business and customer referrals. We hold ourselves and each other to high standards. We expect you to care deeply about the work you do, the products you build, and the experience our customers have in every interaction with us. You must work hard, take ownership from inception to delivery, and approach every problem with an open mind and a positive attitude. We value effectiveness, competence, and a growth mindset. About the Role Forward Deployed Engineers are a customer’s trusted advisor and technical counterpart throughout the lifecycle of their AI workloads. FDEs work across multiple areas of the organization, including software engineering, SRE, infrastructure engineering, networking, solutions architecture, and technical support. FDEs are expected to have strong technical and interpersonal communication skills. You should be able to concisely and accurately share knowledge, in both written and verbal form, with teammates, customers, and partners. As an FDE, your responsibilities are aligned with the success of our customers, and you’ll work side-by-side with them to deeply understand their workloads and solve some of their most pressing challenges. A day’s work may include: Deploying clusters of 1,000+ GPUs using custom written playbooks; modifying these tools as necessary to provide the perfect solution for a customer. 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. Supporting customers as part of an on-call rotation, up to two weeks per month. Focus A customer-centric attitude, an accountability mindset, and a bias to action. A track record of shipping clean, well-documented code in complex environments. An ability to create structure from chaos, navigate ambiguity, and adapt to the dynamic nature of the AI ecosystem. Strong technical and interpersonal communication skills, a low ego, and a positive mental attitude. An ideal candidate meets at least the following requirements: 2+ years of SWE, SRE, DevOps, Sysadmin, and/or HPC engineering experience. Great verbal and written communication skills in English. Experience deploying and operating Kubernetes and/or SLURM clusters. Experience in writing Go, Python, Bash. Experience using Ansible, Terraform, and other automation or IAC tools. Strong engineering background, preferably in Computer Science, Software Engineering, Math, Computer Engineering, or similar fields. Exceptional candidates have one or more of the following experiences: You have built and operated an AI workload at 1000+ GPU scale. You have built multi-tenant, hyperscale Kubernetes based services. You have physically deployed infrastructure in a datacenter, managed bare metal hardware via MaaS or Netbox, etc. You have deployed and managed multi-tenant InfiniBand or RoCE networks. You have deployed and managed petabyte scale all-flash storage systems, including DDN, VAST, and/or Weka; or Ceph, LUSTRE, or similar open source tools. Interview Process After submitting your application, the team reviews resume. If your application passes this stage, you will be invited to a 15 minute hiring manager screen. If you clear the initial phone interview, you will enter the main process, which consists of three 45 minute interviews: a technical deep dive, customer communications and debugging session, and culture fit interview. Our goal is to finish the main process within one week. All interviews will be conducted via virtually. Benefits Competitive total compensation package (cash + equity). Retirement or pension plan, in line with local norms. Health, dental, and vision insurance. Generous PTO policy, in line with local norms. Fluidstack is remote first, but has offices in London, New York, and SF. For all other locations, we provide access to WeWork. #J-18808-Ljbffr Fluidstack

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