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.
Maximise your chances of a successful application to this job by ensuring your CV and skills are a good match.
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 xxuwjjq 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