PD Senior Engineer – Model Lifecycle, Sustainability and MLOps, Pharmaceutical Product Development
Core
Drive model lifecycle sustainability, MLOps frameworks, and operationalization of ML/statistical models for pharmaceutical product development.
Role type
Senior IC MLOps Engineer (Pharma)
Builds
Reusable MLOps capabilities, workflows, and standards for PD's Model Hub
Domain
Pharmaceutical Product Development + MLOps
Deliverable
production ML models
Required skills
MLOps, Python, PySpark, Machine Learning (skLearn, PyTorch), Git, CI/CD, automated testing, model registries, experiment tracking, observability, versioning, governance, Databricks, AWS, MLflow, Docker, Kubernetes, GitHub Actions, Azure DevOps, data drift analysis, model drift analysis
Preferred skills
Model risk management, validation, change control, data integrity, privacy, security, responsible AI, GenAI, AI agents, LLM-powered workflows
Technologies
Databricks, AWS, MLflow, Docker, Kubernetes, GitHub Actions, Azure DevOps, Evidently AI
Responsibilities
Develop and implement MLOps frameworks and best practices; Deploy and operationalize advanced ML/statistical models; Design robust model lifecycle workflows (validation, deployment, monitoring, retraining); Design scalable approaches for model discoverability and governance; Build model observability strategies for performance and drift detection
Seniority
Senior, hands-on IC