Machine Learning Engineering Manager We're building a new ML Engineering team and are looking for a strong technical lead to help take our machine learning capability from proof-of-concept to fully scaled, production-ready solutions. Sitting within our Group & Enterprise Services (GES) function, this role is part of the Data vertical and reports into the Head of Data Engineering. You'll be hands-on with cloud infrastructure, APIs and deployment pipelines, working mainly in GCP Vertex AI (essential) and Azure (desirable). Your focus will be enabling data scientists to deploy high-impact models reliably and at scale. You'll combine leadership, architectural thinking and deep engineering skills to shape the ML platform, coach engineers and deliver robust, enterprise-ready ML services. What you'll do \* Lead, mentor and develop a small team of ML Engineers \* Oversee delivery of ML capabilities and support planning and capacity needs \* Shape architecture from early design through to production \* Build and maintain Python APIs (Flask/FastAPI) for model serving \* Develop infrastructure for real-time and batch deployments \* Design and maintain CI/CD pipelines for models \* Ensure code quality, engineering best practice and scalable cloud deployments \* Collaborate with data scientists, platform engineers and developers \* Support model lifecycle management, monitoring and automation \* Break down solution designs into deliverables and milestones What you'll bring \* 5+ years as an ML Engineer with strong Python engineering skills \* Experience deploying and maintaining ML models in production (Vertex AI required) \* Strong software engineering fundamentals: OOP, unit testing, TDD \* Cloud experience (GCP, AWS or Azure) and IaC tools such as Terraform \* Experience with Docker, CI/CD pipelines and Git workflows \* Understanding of data science principles and taking research code to production \* Strong problem-solving skills and the ability to work independently \* Comfortable working in Agile teams \* Clear communication, collaboration and a proactive, improvement-driven mindset