Senior Machine Learning Engineer

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