ML Engineer

ML Engineer
London – Hybrid, 3 days per week in office
Up to £85,000
VIQU are partnering with a leading financial services organisation undergoing a significant data and technology transformation, building out its Machine Learning capability across the business. They are seeking an ML Engineer to build, deploy and operate production-grade ML solutions, working closely with Data Scientists to take models from development through to reliable production environments. This is a hands-on engineering role focused on ML pipelines, productionisation, deployment and ongoing model lifecycle management within a modern Databricks environment.
Key Responsibilities of the ML Engineer:
Build and automate end-to-end ML pipelines covering feature engineering, model training, scoring and deployment
Productionise models developed by Data Scientists, transforming notebooks and prototypes into modular, tested and production-ready code
Develop scalable ML solutions using Python, PySpark, Databricks and MLflow
Deploy machine learning models into batch and real-time environments through APIs, scheduled workflows and production pipelines
Manage model versioning, promotion and rollback throughout the ML lifecycle
Implement monitoring and observability across production models, including model and data drift, performance alerts and logging
Develop automated retraining processes to maintain model performance and reliability
Work closely with Data Engineering and Platform teams on CI/CD integration, compute optimisation and secure deployment patterns
Maintain strong engineering standards across testing, documentation, code quality, reproducibility and operational reliability
Key Experience Required of the ML Engineer:
Strong commercial experience as an ML Engineer, with a clear focus on engineering and productionising machine learning models
Strong hands-on development skills across Python, PySpark and SQL
Commercial experience working with Databricks, MLflow and Delta Lake
Proven experience building and operating distributed data and machine learning pipelines
Experience taking Data Science models from notebooks or development environments into production
Strong unde...