> Markdown version of [/jobs/ext/329067-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/329067-machine-learning-engineer). 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). --- # Machine Learning Engineer - **Company:** Generative Engineering - **Location:** Slough, UK - **Contract:** Permanent contract - **Skills:** Artificial Neural Networks, Data Infrastructure, Python (Programming Language), Machine Learning, Open Source Technology, Reinforcement Learning, Pytorch, Facebook Flow, Deep Learning, Information Technology, Physical Design, Markov, Data Pipelines - **Published:** June 5, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/x/38262864/ ## About the Role Must HavesPhD in Machine Learning, Computer Science, Applied Mathematics, or a closely related field, with original contributions to deep learning, reinforcement learning, or generative models.Formal background in generative modelling - working knowledge of the transformer architecture, diffusion models, flow matching, and variational autoencoders: their evolution, their tradeoffs, and where they're going.Real world experience building ML/AI systems that reached production, not just research prototypes.Practical experience managing research projects end to end - from problem formulation through to evaluation and deployment.Knowledge of modern, larger-scale Python and the ML stack (PyTorch, JAX, or equivalent). You write research-grade code.Practical experience building large-scale data pipelines. We don't have data infrastructure - you'll help build it. Nice to HaveExperience in a high-pace startup environment.Knowledgeable about physical engineering or related domains such as robotics or cognitive science.Experience working with PINNs (physics-informed neural networks) or graph neural networks for physics-based surrogate models.Experience owning or being involved longer-term in an open source project, ideally in a related field such as ML tooling or scientific computing.Experience with GPU cluster orchestration.Experience with vector embeddings, ideally retrieval-augmented generation (RAG) and multi-modal representations (e.g. CLIP).Experience with model fine-tuning.Experience with Markov chains or (partially-observable) Markov decision processes.Just state the word 'Salmon' anywhere in your application, just to prove you can read a job advert :) We aim to improve all our colleagues' abilities and careers by exposing them to the bare bones of a tech start-up whilst giving them the opportunity to support the company in any way. If our people continuously improve, so does our product. ## Description We are looking for a Machine Learning Engineer to join the team - someone who can operate across the full spectrum from research to production. This role sits closer to the research end: you'll be pushing the frontier on generative models for physical design while also shipping real systems that engineers use every day. Please show both the quality of your past research and any production impact it has had. ## Related Videos - [Rules, Heuristics, or LLMs? Lessons from Solving the Same Problem Twice](https://www.wearedevelopers.com/videos/100112-rules-heuristics-or-llms-lessons-from-solving-the-same-problem-twice) - [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) - [How E.On productionizes its AI model & Implementation of Secure Generative AI.](https://www.wearedevelopers.com/videos/623-how-e-on-productionizes-its-ai-model-implementation-of-secure-generative-ai) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [DALL·E Flow: when neural search meets generative art](https://www.wearedevelopers.com/videos/389-dall-e-flow-when-neural-search-meets-generative-art) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [How machine learning can help us tell fact from fiction](https://www.wearedevelopers.com/magazine/509-how-machine-learning-can-help-us-tell-fact-from-fiction) - [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)