Senior Machine Learning Engineer | Insurance | Manchester (Hybrid)
đź’° 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.
The Opportunity
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.
What You’ll Be Doing
* 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
What They’re Looking For
* 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)
Why This Role?
* 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.
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