Yarnton, Kidlington, Oxfordshire, England, United Kingdom Hybrid / WFH Options
Noir
MachineLearningEngineerMachineLearningEngineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a MachineLearningEngineer to … from concept to production. If you thrive in fast-paced, intellectually charged environments where every model could change an industry, you'll fit right in. Our client is seeking MachineLearning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas … Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push the boundaries of what's possible. All MachineLearningEngineer positions come with the following benefits: * Competitive salary with annual performance-based bonuses * Equity options - share in the company's long-term success * Private healthcare More ❯
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 machinelearning 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 machinelearning 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 machinelearning 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 machinelearning 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 ❯
oxford district, south east england, united kingdom
Alloyed
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 machinelearning 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 machinelearning 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 machinelearning 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 machinelearning 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 MachineLearningEngineer 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, machinelearning, 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 ❯
oxford district, south east england, united kingdom
Llama Recruitment Solutions
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 MachineLearningEngineer 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, machinelearning, 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 ❯