model lifecycle, including training orchestration, experiment tracking, model registries, CI/CD, deployment and monitoring. EstablishMLOpsstandards and engineering practices, including model testing and validation, containerisation, deployment patterns, model packaging, release management and production operations. Establish standards for model artefact management, versioning, lineage and configuration control, ensuring model weights, parameters, hyperparameters … production. Strong software engineering skills,includingproficiency in Python, and experience building scalable production-grade platforms and tooling, along with a deep understanding of containerisation and orchestration technologies such as Docker, Kubernetes and Helm. Strong collaboration and influencing skills, with the ability to work effectively across research, engineering and business teams. ...