> Markdown version of [/jobs/ext/3019245-research-engineer-ai-deep-learning-llm](https://www.wearedevelopers.com/jobs/ext/3019245-research-engineer-ai-deep-learning-llm). 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). --- # Research Engineer - AI / Deep Learning / LLM - **Company:** Projectscollaborating - **Location:** London, UK - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, C++ (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Large Language Models, Deep Learning, Generative AI - **Published:** September 21, 2026 - **Apply:** https://www.apply4u.co.uk/jobs/research-engineer-ai-deep-learning-llm/47382414 ## About the Role techniquesProficiency in Python, C++ or similar languagesStrong problem-solving skills and the ability to work both independently and collaborativelyGood communication skills, with the ability to document and explain technical work clearlyNice to haveExperience with optimisation, reinforcement learning and/or large language modelsFamiliarity with deep learning frameworks such as TensorFlow, PyTorch or JAXExperience building and maintaining research infrastructure or toolsExposure to chip design or applied AI research #J-18808-Ljbffr ## Description Research Engineer - AI / Deep Learning / LLMOur client's research team applies AI to the design and optimisation of semiconductors, alongside fundamental research that supports both internal applications and the broader scientific community. Current areas of interest include large language models, optimisation methods for deep learning, reinforcement learning and generative models.This is a permanent role working 100% onsite in either London or CambridgeWhat you will be doingImplementing and testing research ideas in machine learning and AIBuilding prototypes and supporting experiments for team and company projectsCollaborating with researchers to translate theoretical models into practical systemsMaintaining and improving research infrastructure, tools and workflowsAssisting in the preparation of technical documentation and reportsStaying up to date with the latest advancements in AI and related fieldsWhat we are looking forExperience implementing machine learning algorithms and ## Related Videos - [Getting Started with Machine Learning](https://www.wearedevelopers.com/videos/260-getting-started-with-machine-learning) - [Inside the Mind of an LLM](https://www.wearedevelopers.com/videos/1617-inside-the-mind-of-an-llm) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [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) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation](https://www.wearedevelopers.com/videos/612-fireside-chat-deep-learning-deep-impact-harnessing-ai-for-language-innovation) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline) - [Dev Digest 132 - Binging WADFlix?](https://www.wearedevelopers.com/magazine/473-dev-digest-132-binging-wadflix) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)