GenAI ML Engineer - Payment Integrity

GenAI/Machnie Learning Engineer - Remote Opportunity A growing healthcare organization is looking for a Machine Learning Engineer to support key initiatives across Risk Adjustment and Payment Integrity. This role focuses on building and scaling practical ML solutions that improve coding accuracy, streamline clinical review, and enhance claims analysis.

Responsibilities:

Build and deploy ML-driven solutions to support clinical review, coding accuracy, and claims analysis Work with structured data (e.g., data warehouse) and unstructured data (clinical documents, PDFs) Develop pipelines for model training, evaluation, and deployment Support chart review workflows, suspect identification, and payment integrity use cases Integrate models and tools into production systems used by operations and clinical teams Troubleshoot data and performance issues, ensuring systems remain reliable and efficient Collaborate with engineering, clinical, and business stakeholders to improve workflows and outcomes

Qualifications:

5+ years of experience in machine learning, data science, or a related field Strong Python skills and experience building and maintaining ML pipelines Experience working with healthcare data, ideally in: Medicare Advantage Risk Adjustment or HEDIS Payment Integrity / claims workflows Familiarity with cloud platforms (GCP preferred) Experience working with structured and document-based data Ability to troubleshoot, analyze, and improve existing systems Strong communication skills and ability to work cross-functionally A practical, problem-solving mindset and comfort working in a fast-paced environment If you meet the qualifications for this role, please apply now! First round interviews are being scheduled ASAP.