Senior Machine Learning Engineer

Senior Machine Learning Engineer | Insurance | Manchester (Hybrid)

💰 Competitive base + discretionary bonus + strong pension & benefits

We’re partnering with a leading specialty insurance business that’s investing heavily in its enterprise data and machine learning platform, built around a modern Databricks Lakehouse. The goal: move away from fragmented legacy systems and unlock real business value from data across underwriting, claims and finance - at scale and in production.

This is a senior, hands-on machine learning engineering role where you’ll own production ML models end to end, working within cross-functional squads to deliver robust, well-governed solutions in a highly regulated, data-rich environment.

You’ll sit at the heart of a growing ML capability, designing, deploying and operating machine learning models that directly influence strategic decision-making across the business.

This role blends deep technical ownership with real stakeholder impact — ideal for an experienced ML Engineer who enjoys taking models from idea to production, embedding strong MLOps practices, and building systems that stand up to audit, scale and change.

• Leading the end-to-end design, development, testing, deployment and monitoring of production ML models on Databricks
• Establishing and embedding best-practice MLOps standards including versioning, governance, monitoring and retraining strategies
• Building automated testing frameworks for ML models (unit, integration, regression and bias testing)
• Partnering with stakeholders to translate business problems into appropriate ML approaches, managing ethical and privacy considerations
• Defining KPIs and reliability measures for production ML systems
• Producing high-quality model documentation covering assumptions, methods, metrics and failure modes
• Ensuring full data and model traceability, supporting audit and regulatory requests
• Diagnosing and resolving production ML issues with a structured, evidence-based approach
• Collaborating closely with data engineers, analysts and business teams in Agile squads
• Coaching and educating wider teams on ML techniques and best practice
• Keeping pace with advances in machine learning and Databricks, proposing improvements and innovations

• Strong background in machine learning, data science and/or data engineering
• Advanced Python, SQL and PySpark skills, writing scalable, production-grade code
• Hands-on experience establishing and running MLOps processes on Databricks
• Experience building pipelines for structured and unstructured data
• Solid understanding of statistics and model evaluation techniques
• Comfortable working autonomously while thriving in Agile, cross-functional teams
• Strong communicator able to explain complex technical concepts to non-technical stakeholders
• Insurance or financial services experience strongly preferred (regulated environments a plus)

• Own production ML models end to end — not experimentation-only work
• Strong investment in Databricks, Lakehouse architecture and modern MLOps
• High visibility and influence across the business
• Work on meaningful insurance ML problems with real-world impact
• Hybrid working and a collaborative, mature engineering culture
• Excellent benefits covering financial, physical and mental wellbeing

If you’re a Senior Machine Learning Engineer looking to build scalable, well-governed ML systems in a forward-thinking insurance environment — let’s talk.