Job Description:
AI/ML Engineer - US Healthcare Claims ManagementPosition: MLOps Engineer - US Healthcare Claims Management
Location
: Gurgaon, (Hybrid)
Company
: Neolytix
Experience Required-
3 to 5 years
Preference will be given to candidates holding a PHD in the relevant field.
About the Role:
We are seeking an experienced MLOps Engineer to build, deploy, and maintain AI/ML systems for our healthcare Revenue Cycle Management (RCM) platform. This role will focus onoperationalizing machine learning models that analyze claims, prioritize denials, and optimize revenue recovery through automated resolution pathways.
KeyTechStack:
Models & ML Components:
- 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/HuggingFaceTransformers
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.
PreferredQualifications:
- Experience with healthcare data, particularly claims processing (EDI 837/835)
- Knowledge of RCM workflows & denial management processes
- Understanding of HIPAA compliance requirements.
- Experience with feature stores & model registries
- Familiarity with healthcare-specific NLP applications
What Sets You Apart:
- 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
What We Offer:
- Competitive salary and benefits package.
- Opportunity to contribute to innovative AI solutions in the healthcare industry.
- Dynamic and collaborative work environment.
- Opportunities for continuous learning and professional growth.
To Apply: Submit your resume and a cover letter detailing your relevant experience and interest in the role to [email protected]
