Senior AI Engineer

Leading with our core values of Quality, Integrity, and Opportunity, Med Insight is one of the healthcare industry’s most trusted solutions for healthcare intelligence. Our company purpose is to empower easy, data-driven decision-making on important healthcare questions. Through our products, education, and services, Med Insight is making an impact on healthcare by helping to drive better outcomes for patients while reducing waste.

Over 300 leading healthcare organizations have come to rely on Med Insight analytic solutions for healthcare cost and care management. Med Insight has been ranked #1 for Payer Quality Analytics by clients for the last three years in the Best in KLAS report.

Med Insight is a subsidiary of Milliman; a global, employee-owned consultancy providing actuarial consulting, retirement funding and healthcare financing, enterprise risk management and regulatory compliance, data analytics and business transformation as well as a range of other consulting and technology solutions.

We’re seeking a Senior AI Engineer with deep expertise in healthcare claims and machine learning to design, build, and deploy production-grade AI systems. You’ll work across platform engineering, data science, product, and clinical teams to create solutions that improve healthcare quality, risk adjustment, and population health insights. This role blends traditional ML, MLOps, and generative AI (Gen AI) to drive impactful analytics products.

• MIKE (Med Insight Knowledge Engine): AI-assistant for healthcare analytics
• Data Confidence Model (DCM): AI-enhanced data validation and quality assurance
• Risk Adjustment AI
  : HCC recapture, risk scoring automation and predictive modeling
• Claims Analytics AI
  :
  Pattern recognition, fraud detection, and utilization forecasting
• Population Health Models
  :
  Member segmentation, risk stratification, and predictive analytics
• Healthcare NLP
  :
  Clinical coding, documentation improvement, and insights extraction
• Lakehouse AI Integration
  :
  Embedding AI across our healthcare data platform

• Design, build, and deploy production ML models and MLOps pipelines
• Engineer feature-rich solutions for healthcare claims, risk prediction, and population health
• Implement scalable inference systems with proper validation, monitoring, and performance tracking
• Strategically integrate LLMs and Gen AI into analytics products, building RAG systems and conversational interfaces
• Collaborate with engineering, product, and clinical teams to translate business needs into AI solutions
• Ensure models meet clinical accuracy, regulatory compliance, and business credibility
• Contribute to ML strategy, tooling, and best practices across teams

• 5+ years of ML engineering experience with production deployments
• Strong Python skills; familiarity with scikit-learn, XGBoost, PyTorch, Tensor Flow
• Experience with supervised/unsupervised learning, feature engineering, model evaluation, and MLOps
• Cloud ML platform experience (Azure ML, Databricks, Sage Maker) and containerization (Docker/Kubernetes)
• Knowledge of generative AI, LLMs, prompt engineering, and RAG systems

• 3+ years working with healthcare claims data (medical, pharmacy, eligibility)
• Experience with population health analytics, risk adjustment (CMS-HCC, HHS-HCC), and quality measures
• Familiarity with actuarial forecasting, cost trending, and healthcare operations

• Strong cross-functional collaboration skills, able to work with engineers, product managers, and clinical experts
• Able to translate technical concepts for non-technical stakeholders
• Ownership mentality: seeing initiatives from concept to production

• Advanced degree (MS/PhD) in Computer Science, Statistics, Applied Math, or related field
• Experience with healthcare analytics platforms (Med Insight, Health Edge, Cotiviti)
• Knowledge of HEDIS, Star Ratings, and quality improvement programs
• Clinical NLP or medical coding experience
• HIPAA compliance and healthcare data security knowledge

• Languages:
  
  Python, SQL, Py Spark
• ML Engineering:…