2 of 2 Machine Learning Engineer Jobs in Oxford

in the UK, 1 in Japan, and 1 in Seattle to build the future of advanced metal components. To do this it uses proprietary software packages which combine advanced machine learning and physical modelling to invent better alloys, devise better ways to process them, and design better 3D-printed components. Responsibilities Design, develop and validate novel machine learning models to optimize manufacturing processes and material composition Collaborate closely with process engineers, material scientists and other domain experts to identify and engineer the most meaningful features Develop Alloyed’s machine learning platforms to facilitate adoption and application of validated models Work as part of a fast-paced, agile development team Identify and prioritize … 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 Experience with MLOps tools and practices, including Airflow, MLflow, and containerization (e.g., Docker More ❯

innovative, fast-scaling MedTech company that's redefining how lung cancer and lung diseases are diagnosed and treated, using cutting-edge AI. This is an excellent opportunity for a Machine Learning Engineer eager to contribute technical expertise and take ownership in a fast-moving environment with strong potential for growth. You’ll play a key role in … 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 and supporting … ML models in production Excellent communicator across technical teams and stakeholders Effective problem-solver who takes initiative in complex production settings Experience with scientific computing, deep learning, big data, or health IT ontologies (e.g., PyTorch, JAX, Spark, HL7, FHIR) (desirable) Familiarity with cloud infrastructure (Azure/AWS), infrastructure as code, Kubernetes, Linux, Docker, data pipelines, and MLOps tools (desirable More ❯