Senior Machine Learning Engineer Location Manchester, United Kingdom (Hybrid working) Why Apply? This is an opportunity to shape how enterprise machine learning is delivered at scale within a modern data environment. Working on a strategic Lakehouse platform built on Databricks, you will influence how production ML models are designed, governed and optimised, helping the business turn complex data into reliable, decision-driving insight. The role combines hands-on engineering with MLOps leadership, strong stakeholder engagement and long-term platform thinking. Responsibilities * Lead the design, build, deployment and monitoring of production machine learning models using Databricks, ensuring performance, reliability and continuous improvement * Define and embed MLOps best practices including model versioning, governance, access control, monitoring and retraining strategies * Develop automated model validation tests covering unit, integration, regression and bias checks * Translate business problems into effective ML solutions, managing ethical, privacy and data governance considerations * Establish model performance KPIs, reliability measures and production monitoring frameworks * Document model design, assumptions, metrics, risks and failure scenarios, ensuring full data and model traceability * Diagnose and resolve production ML issues, leading root cause analysis and system improvements * Work within cross-functional agile teams and support knowledge sharing across the wider business Requirements * Degree in a STEM subject or equivalent experience with strong statistical understanding * Proven experience delivering machine learning models into production environments * Strong Python, SQL and PySpark skills for scalable, production-grade development * Hands-on experience establishing MLOps processes within Databricks * Experience building data pipelines for structured and unstructured data * Strong stakeholder communication skills, able to explain technical concepts to non-technical audiences * Experience working in agile delivery environments and managing shifting priorities What's in it for me? * Hybrid working model * Discretionary bonus * Non-contributory pension * Private medical and dental cover (including family options) * Life insurance and wellbeing-focused benefits * Supportive, collaborative data and technology environment * Opportunity to work on modern ML, MLOps and Lakehouse technologies at scale