London - Hybrid working

We are partnering with a rapidly growing financial services business that is investing heavily in its machine learning and data platform capabilities. This is a hands‑on engineering role focused on helping Data Science teams build, deploy, and scale machine learning solutions in production. The work sits at the intersection of data engineering, machine learning engineering, and MLOps, with a strong focus on production systems, feature engineering, workflow orchestration, and model lifecycle management.

What you'll be doing

• Design and build scalable data and feature engineering pipelines to support machine learning workloads
• Work closely with Data Scientists to operationalise models and improve the end-to-end machine learning lifecycle
• Develop and optimise PySpark-based data processing workflows and training pipelines
• Build and maintain workflow orchestration frameworks using tools such as Airf...