PD Senior Engineer – Model Lifecycle, Sustainability and MLOps, Pharmaceutical Product Development
Core
Senior Engineer driving 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 / Machine Learning Operations
Deliverable
production ML models
Required skills
MLOps, Python, PySpark, Machine Learning, data drift analysis, model drift analysis, CI/CD, automated testing, model registries, experiment tracking, observability, versioning, governance
Preferred skills
model risk management, GenAI, AI agents, LLM-powered workflows, human-in-the-loop controls
Technologies
Databricks, AWS, MLflow, Docker, Kubernetes, GitHub Actions, Azure DevOps, Lakehouse Monitoring, Evidently AI, scikit-learn, PyTorch
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; Capture lineage and metadata for model reuse
Seniority
Senior, hands-on IC
