We're looking for a highly skilled Machine Learning Engineer to join our data and analytics team. You'll design, build, and optimize scalable, high-performance data pipelines and ML workflows on Databricks, leveraging PySpark, Unity Catalog, and modern data lake house technologies such as Delta Lake and Apache Iceberg. This is an exciting opportunity to shape our ML infrastructure and production pipelines, working at the intersection of data engineering and applied machine learning.
Requirements
- Architect and implement high-throughput data pipelines using PySpark on the Databricks platform to support large-scale ML workloads.
- Develop and operationalise ML workflows and model pipelines leveraging industry-leading frameworks and MLOps practices.
- Drive data governance and metadata management via feature stores to ensure data quality, lineage and compliance.
- Work with modern data lake house storage formats such as Delta Lake and Apache Iceberg to deliver reliable, performant data architectures.
- Collaborate across cross-functional teams including data engineering, data science, analytics and product to translate business challenges into scalable ML solutions.
- Monitor, tune and optimise the performance, cost-efficiency and reliability of data/ML pipelines in a production environment.
- Stay abreast of emerging technologies and best practices in data engineering, ML infrastructure and pipeline design to lift our platform continuously.
Benefits
- Parental leave
- Medical benefits
- Paid sick leave
- Dotdigital day
- Share reward
- Wellbeing reward
- Wellbeing Days
- Loyalty reward
- DEI commitment
