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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Scientist - **Company:** Qureight Ltd - **Location:** Cambridge, UK - **Experience:** Expert - **Salary:** £58,009.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Computer Vision, Code Review, Dicom, Python (Programming Language), Machine Learning, Graphics Processing Unit (GPU), Cloud Platform System, Pytorch, Large Language Models, Deep Learning, Git, Programming Languages - **Published:** July 31, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5821153796 ## About the Role * Strong experience in machine learning research, with experience in either computer vision, foundation models, or 3D medical imaging. * Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation. * Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases. * Experience developing and evaluating deep learning models for imaging, segmentation, classification, regression or representation learning. * Experience with self-supervised learning, foundation models or large-scale model training. * Experience writing production-quality or research-to-production Python code. * Experience with modern software development workflows, including git, pull requests, code review, documentation and ticketing. * Strong communication skills and ability to work across ML, data science, clinical science and engineering teams. * Ability to be proactive, self-sufficient and rigorous when completing tasks. * Strong knowledge of Linux shells, git and modern Python development tools such as uv, poetry, ruff, black, mypy or ty. Even better if you have * Experience with volumetric CT, medical imaging, DICOM, NIfTI or NRRD data. * Experience training models across multiple GPUs or compute nodes. * Experience with cloud environments. * Experience with typed Python or typed programming languages. * Publication record in machine learning, computer vision, medical imaging or related fields. * Experience working in clinical trial, pharmaceutical, biotech or regulated healthcare environments. ## Description As Qureight scales its AI-driven imaging platform and expands its work with pharmaceutical and clinical partners, we are building the machine learning research capability required to develop robust, clinically meaningful models for 3D medical imaging. We are looking for a Senior Machine Learning Scientist to research, develop and specialise state-of-the-art deep learning models for volumetric CT data. The role focuses on foundation-model pre-training, supervised model specialisation, segmentation, classification, regression and biomarker extraction pipelines that support clinical-trial and real-world evidence programmes. This role sits within the Machine Learning function and works closely with ML Engineers, Data Scientists, Clinical Scientists and Imaging Specialists to ensure that research ideas are translated into reproducible model development workflows and clinically useful outputs. What you will do * Research, develop, and evaluate state-of-the-art computer vision methods for volumetric CT data. * Contribute to self-supervised pre-training of large foundation models for 3D vision. * Train and specialise models for supervised tasks, including segmentation, classification and regression. * Keep up to date with the latest machine learning research and contribute to internal reading groups. * Contribute to the publication of high-impact conference, journal and sponsor-facing scientific outputs. * Write high-quality Python and PyTorch code for model training, inference and evaluation. * Translate model outputs into biomarkers that support clinical-trial endpoints, enrichment strategies and disease-characterisation workflows. * Work with clinical and scientific stakeholders to ensure model objectives are clinically meaningful. * Train large models across GPUs and compute nodes, working with ML Engineers to improve performance and scalability. * Work proactively, communicate progress clearly and identify risks early. ## Related Videos - [Running Secure Life Science Research at Scale using Hybrid GPU HPC and Kubernetes 🧬](https://www.wearedevelopers.com/videos/100355-running-secure-life-science-research-at-scale-using-hybrid-gpu-hpc-and-kubernetes) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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