> Markdown version of [/jobs/ext/2789706-developer-experience-devex](https://www.wearedevelopers.com/jobs/ext/2789706-developer-experience-devex). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Developer Experience / DevEx - **Company:** Fractile - **Location:** Bristol, UK - **Contract:** Permanent contract - **Skills:** C++ (Programming Language), Nvidia CUDA, Python (Programming Language), OpenCL, Software Engineering, Rust (Programming Language), Pytorch, Large Language Models - **Published:** September 8, 2026 - **Apply:** https://www.collegerecruiter.com/job/2845713377-developer-experience--devex ## About the Role As a member of the Developer Experience team you will need to understand the current state of development for inference hardware. You will need to be able to identify what will work well for engineers wanting to identify potential opportunities for performance improvements, while knowing what tooling will fit into an existing LLM engineer's workflow with the minimal amount of disruption and effort., We're looking for someone who is self-driven and capable of identifying tooling opportunities, designing those tools, and delivering them in a way which will fit in with an LLM engineer's existing toolset. You will have worked in this area before, possibly as an FDE or at a company that provides inference services using their own models, and have the ability to develop new tools that are designed to be functional and easy to learn and use., * Experience with inference frameworks such as JAX and/or PyTorch * Experience of software development in Python, Rust, C/C++, or a similar language * Experience monitoring and optimising code written in CUDA, ROCm, OpenCL, or similar * Experience monitoring and optimising LLM deployments with 50+ billion parameters * Experience working with stakeholders across multiple teams ## Related Videos - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 157: CUDA in Python, Gemini Code Assist and Back-dooring LLMs](https://www.wearedevelopers.com/magazine/557-dev-digest-157-cuda-in-python-gemini-code-assist-and-back-dooring-llms) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)