About this role

Build the evaluation and validation framework for all agent-driven clinical recommendations
Develop patient risk stratification models for adherence prediction, adverse event likelihood, dosage titration optimization, and churn/dropout risk
Implement and manage the predictive analytics pipeline on AWS
Design and build the RAG architecture that grounds agent responses in clinical protocols
Own model lifecycle management
Build explainability layers for clinical recommendations
Collaborate with the clinical team to translate clinical protocols and pharmacy domain knowledge into model features, training labels, and validation criteria
Establish model monitoring and alerting

6+ years in ML engineering or applied data science, with at least 3 years shipping ML models to production in a healthcare, biotech, or clinical domain
Direct experience building clinical decision support, risk stratification, or patient outcome prediction models
Production experience with LLM-based agent systems
Demonstrated ability to collaborate with clinical domain experts (physicians, pharmacists, clinical researchers)
Experience working in HIPAA-regulated environments
Track record of building explainable models in regulated contexts

Machine Learning Engineer

Key skills