3 of 3 Computer Vision Jobs in Oxford

and MLflow for experiment tracking, model registry, and lifecycle management, ensuring strong CI/CD practices and model governance Essential Skills Bachelor’s degree in science, engineering, mathematics or computer science (2:1 minimum) Strong python development skills Practical experience in the development of machine learning models and/or deep learning to solve complex science and engineering problems … and practices, including Airflow, MLflow, and containerization (e.g., Docker) A passion for gaining insight into real-world datasets and clearly communicating through data visualization techniques Interest in material discovery, computer vision, handling big data and optimisation techniques Highly effective communicator who encourages innovation through collaboration Natural problem-solver with a desire to learn Organised and self-motivated Desired More ❯

competitive edge Participate in Agile processes, including planning and standups Support and enhance cloud and CI/CD infrastructure. Troubleshoot and resolve production challenges Ideal candidate 3yrs+ experience in computer vision, machine learning, bioinformatics, or medical informatics Proven ability to build maintainable, secure, and high-performance solutions Strong proficiency in Python and modern ML frameworks Skilled in deploying More ❯

journey modelling. About the Roles & Responsibilities Protein & DNA Modelling – building and adapting ML models to biological sequence and structure data, often leveraging foundation models such as ESM and EMO. Computer Vision & 3D Reconstruction – developing applied AI solutions for imaging data, including phenotyping, microscopy, and sensor-based reconstruction systems. LLM Engineering for Autonomous Labs – designing and deploying large language … models to automate experimental workflows and scientific protocols. Qualifications PhD in Computer Science or related field 3-7 years experience in Biotech, Clinical or related Industry Hands-on experience with model development, deployment, and adaptation (beyond theoretical work). Experience working with real-world data (imaging, biological, or EHR-based). The ability to collaborate effectively across research, engineering More ❯