PD Senior Engineer – Model Lifecycle, Sustainability and MLOps, Pharmaceutical Product Development

Overview

Senior Engineer for Model Lifecycle Sustainability and MLOps in Pharmaceutical Product Development, focusing on reproducible, observable, governed, and valuable ML/statistical models after deployment.

What you'll do

• Contribute to development and implementation of MLOps frameworks, standards, and best practices with IT and Data Scientists.
• Deploy and operationalize advanced ML, statistical, and data-driven models within PD’s Model Hub.
• Develop end-to-end model lifecycle workflows covering validation, deployment, monitoring, retraining, versioning, and continuous improvement.
• Design approaches for model discoverability, reproducibility, and governance.
• Build model observability to monitor model performance, data drift/model drift, and infrastructure health with alerting mechanisms.
• Enable model discoverability and reuse using lineage and metadata capture through PD’s Model Hub.

What you'll need

• At least 4 years of industry experience with MLOps practices including Git, CI/CD, automated testing, model registries, experiment tracking, observability, versioning, and governance.
• Degree in Computer Science, Engineering, Statistics, Data Science, or a related discipline.
• Hands-on experience with Databricks, AWS, MLflow, Docker, Kubernetes, GitHub Actions, Azure DevOps, Lakehouse Monitoring, and Evidently AI.
• Strong expertise in Python and PySpark, and knowledge of Machine Learning including scikit-learn and PyTorch.
• Practical expertise in data drift and model drift analysis, including baseline design, metric selection, thresholding, root-cause analysis, and remediation decisions.
• Experience deploying, operating, monitoring, and maintaining production ML solutions across multiple lifecycle stages.
• Ability to translate scientific and technical needs into scalable platform capabilities and adoption roadmaps.

Details

• Location: Hyderabad - TS - IN.