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