Role: AI/ML Engineer Healthcare
Location : Remote
Duration : 6 Months
1. Customize and fine tune existing healthcare ML models for client specific populations and use cases.
2. Build, train, retrain, and evaluate ML models for Risk Stratification and population health analytics.
3. Develop feature engineering pipelines using healthcare data (claims, EHR, labs, SDoH).
4. Implement reproducible ML pipelines with experiment tracking and dataset versioning.
5. Deploy models to production using batch and/or real time inference patterns.
6. Monitor model performance, data quality, drift, and bias in production environments.
7. Implement automated testing and validation for model accuracy, stability, and reliability.
8. Ensure secure handling of PHI and compliance with HIPAA engineering requirements.
9. Produce model documentation including assumptions, features, performance metrics, and limitations.
10. Collaborate with architects, data engineers, and product teams to deliver production ready AI solutions.
Key Skills: AI/ML, Healthcare industry, Risk Stratification, healthcare data