Machine Learning Intern

As a Machine Learning Operations (MLOps) Engineer at Neolytix working on US Healthcare Claims Management, your role will involve building, deploying, and maintaining AI/ML systems for the healthcare Revenue Cycle Management (RCM) platform. You will be responsible for operationalizing machine learning models to analyze claims, prioritize denials, and optimize revenue recovery through automated resolution pathways. **Key Responsibilities:** - Design and implement end-to-end ML pipelines for claims processing, including automated training, testing, and deployment workflows - Deploy and orchestrate LLMs and SLMs in production using containerization (Docker/Kubernetes) and Azure cloud services - Implement monitoring systems to track model performance, drift detection, and operational health metrics - Establish CI/CD pipelines specifically for ML model training, validation, and deployment - Create robust data preprocessing pipelines for healthcare claims data, ensuring compliance with HIPAA standards - Tune and optimize models for performance and cost-efficiency in production environments - Implement Infrastructure as Code (IaC) practices for reproducible ML environments and deployments - Document technical solutions and create best practices for scalable AI-driven claims management **Qualifications Required:** - Experience operationalizing LLMs for domain-specific enterprise applications - Background in healthcare technology or revenue cycle operations - Track record of improving model performance metrics in production systems As part of the Neolytix team, you can look forward to a competitive salary and benefits package, the opportunity to contribute to innovative AI solutions in the healthcare industry, a dynamic and collaborative work environment, and opportunities for continuous learning and professional growth. If this role aligns with your expertise and interests, you can apply by submitting your resume and a cover letter to vidya@neolytix.com.,