duplicated effort and accelerate delivery across multiple Data Science teams. Drive the adoption of modern software engineering practices, including automated testing, infrastructure as code, containerisation, CI/CD, IaC, model versioning, and production monitoring. Support orchestration and automation of ML workloads using tools such as Prefect, AWS-native services …/CD pipelines for software, data, and machine learning workflows. Strong Python engineering skills and experience building maintainable, tested, production-ready code. Experience with containerisation using Docker, and ideally deployment on ECS, EKS, Kubernetes, or equivalent platforms. Good understanding of model training, batch inference, real-time inference, model monitoring, retraining ...