ML / Data Engineer – Data Science Enablement

Role Overview

This role will support the Rare Disease Business Unit (RDBU) patient finding team, working closely with data scientists to build scalable pipelines, productionize models, and establish robust evaluation and monitoring frameworks. The candidate will report to the Data Science Enablement Manager and work on productionalizing advanced patient finding models in a rare disease context.

What You Will Do

Build and maintain scalable data and ML pipelines, productionize machine learning models, design and implement model evaluation and monitoring frameworks, enable end-to-end ML lifecycle management, and partner with RDBU data science teams.

Why It Might Be a Fit

The role offers exposure to end-to-end ML systems and real-world deployment challenges, close collaboration with data scientists on high-impact commercial use cases, and the opportunity to shape ML engineering and enablement standards at scale.

Requirements

• Bachelor’s or Master’s in Computer Science, Data Engineering, or related technical field
• 3–5 years of experience in ML engineering, data engineering, or related roles
• Strong programming skills in Python and SQL
• Experience with data pipeline development and distributed computing (e.g., Spark/PySpark)
• Working knowledge of Databricks and at least one cloud platform (AWS, Azure, or GCP)
• Experience with ML lifecycle tools (e.g., MLflow, Git, CI/CD pipelines)
• Understanding of model deployment, monitoring, and reproducibility practices