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Fractile

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Developer Experience Engineer

BristolOn-site

AI Summary

At Fractile, we're taking a revolutionary approach to computing to run the world's largest language models at scale. Building silicon, systems and software that redefine the frontier of AI only matters if developers can actually get their models running on it quickly and predictably, which is where you come in.

About this role

At Fractile, we're taking a revolutionary approach to computing to run the world's largest language models at scale. Building silicon, systems and software that redefine the frontier of AI only matters if developers can actually get their models running on it quickly and predictably, which is where you come in.

We're looking for Developer Experience Engineers to build the tooling and workflows that companies will use to optimise their large language models onto our next-generation inference hardware.

In this role, you will:

  • Design and build the tools that customers use to run, optimise, and monitor large language models on Fractile hardware.
  • Build the interfaces to existing diagnostic, profiling, and observability tools that let developers understand performance profiles, debug issues, and optimise their deployments.
  • Write the documentation, quickstarts, reference examples, and tutorials that define a developer's first and lasting impression of our platform.
  • Act as the voice of the external developer inside Fractile — turning real deployment pain into roadmap priorities.
  • Work in a tight hardware-software co-design loop with ML compiler, runtime, systems software, and silicon engineers to shape APIs and abstractions before they ossify.

It would be great if you have:

  • Strong software engineering fundamentals and experience building developer-facing tooling, SDKs, APIs, or platforms that other engineers depend on.
  • Excellent Python skills, with solid experience of one or more systems languages such as Rust, C++, or Go.
  • A good understanding of modern ML workloads and the practical challenges of deploying large language models to production.
  • Empathy for the developer experience — you instinctively reduce the number of steps, surprises, and footguns between a user and a working result.
  • A creative and innovative mindset, and a willingness to take ownership and drive results in a fast-paced environment.
  • A Computer Science, Electronic Engineering, Maths, Physics, or related degree and 5+ years of industry experience.

You may also have:

  • Experience with inference serving stacks (vLLM, SGLang, TensorRT-LLM, Triton) or ML compiler and runtime toolchains.
  • Experience working with GPUs, TPUs, or other machine learning accelerators.
  • A track record of contributing to or maintaining open source developer tools or ML ecosystem projects.
  • Experience writing technical documentation and developer education content.
  • Previous experience in a startup or small team environment.

How we work

  • Ownership and execution: you will have full agency to drive your work forward.
  • Hyrid: Three days per week working on-site
  • Rapid iteration: we all work directly with top leadership to move from idea to product on ambitious timelines.
  • Full-stack engagement: hardware, software, silicon, and modelling teams all work closely together to create a product with generational impact.
  • Optimistic and pragmatic: we possess the will to win, and to do the hard work to get us there.
  • Team player mentality: the mission is bigger than any of us, and we have the curiosity and technical focus to see the best idea shipped, no matter whose it is.

About us

  • Founded in 2022, with a team of 100+ that is expanding rapidly.
  • Modern, open offices in London and Bristol.
  • A collaborative, problem-solving culture built on deep curiosity, entrepreneurial initiative and technical fluency.

Export control and security clearance

Certain roles may involve working on technologies subject to export restrictions. Applicants may be required to undergo additional eligibility checks to ensure compliance with applicable law.



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