About the Role:

Key Tech Stack:

• Fine-tuned healthcare LLMs (GPT-4, Claude) for complex claim analysis
• Knowledge of Supervised/Unsupervised Models, Optimization & Simulation techniques
• Domain-specific SLMs for denial code classification and prediction
• Vector embedding models for similar claim identification
• NER models for extracting critical claim information
• Seq2seq models (automated appeal letter generation)

Languages & Frameworks:

• Strong proficiency in Python with OOP principles - (4 years of experience)
• Experience developing APIs using Flask or Fast API frameworks – (2 years of experience)
• Integration knowledge with front-end applications – (1 year of experience)
• Expertise in version control systems (e.g., GitHub, GitLab, Azure DevOps) - (3 years of experience)
• Proficiency in databases, including SQL, NoSQL and vector databases – (2+ years of experience)
• Experience with Azure (2+ years of experience)

• Libraries: PyTorch/TensorFlow/Hugging Face Transformers

Key Responsibilities:

• ML Pipeline Architecture: Design and implement end-to-end ML pipelines for claims processing, incorporating automated training, testing, and deployment workflows
• Model Deployment & Scaling: Deploy and orchestrate LLMs and SLMs in production using containerization (Docker/Kubernetes) and Azure cloud services.

• Monitoring & Observability: Implement comprehensive monitoring systems to track model performance, drift detection, and operational health metrics.

• CI/CD for ML Systems: Establish CI/CD pipelines specifically for ML model training, validation, and deployment.

• Data Pipeline Engineering: Create robust data preprocessing pipelines for healthcare claims data, ensuring compliance with HIPAA standards.

• Model Optimization: Tune and optimize models for both performance and cost- efficiency in production environments

• Infrastructure as Code: Implement IaC practices for reproducible ML environments and deployments.

• Document technical solutions & create best practices for scalable AI-driven claims management.

Preferred Qualifications:

• Experience with healthcare data, particularly claims processing (EDI 837/835)