Job Description
We are seeking an experienced MLOps Engineer to build, deploy, and maintain AI/ML systems for our US Healthcare Claims Management platform. This role focuses on operationalizing machine learning models to analyze claims, prioritize denials, and optimize revenue recovery through automated resolution pathways. You will be responsible for designing and implementing end-to-end ML pipelines, deploying and scaling LLMs and SLMs, implementing monitoring systems for model performance, and establishing CI/CD pipelines for ML model training and deployment. Additionally, you will create robust data preprocessing pipelines for healthcare claims data, tune models for performance and cost-efficiency, implement IaC practices, and document technical solutions.
Good To Have:
- Experience with healthcare data and claims processing
- Knowledge of RCM workflows and denial management
- Understanding of HIPAA compliance
- Experience with feature stores and model registries
- Familiarity with healthcare-specific NLP applications
- Experience operationalizing LLMs for enterprise applications
- Background in healthcare technology or revenue cycle operations
- Track record of improving model performance metrics
Must Have:
- Strong proficiency in Python with OOP principles (4 years exp)
- Experience developing APIs using Flask or Fast API (2 years exp)
- Expertise in version control systems (3 years exp)
- Proficiency in databases (SQL, NoSQL, vector DBs) (2+ years exp)
- Experience with Azure (2+ years exp)
- Experience with PyTorch, TensorFlow, or Hugging Face Transformers
- Design and implement ML pipelines
- Deploy and orchestrate LLMs and SLMs
- Implement monitoring systems for model performance
- Establish CI/CD pipelines for ML
- Create data preprocessing pipelines
- Tune and optimize models
- Implement IaC practices
- Document technical solutions
Perks:
- 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
Job Description: AI/ML Engineer - US Healthcare Claims Management
Position: 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.
operationalizing machine learning models that analyze claims, prioritize denials, and optimize revenue recovery through automated resolution pathways.
Position: 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.
Key Tech Stack:
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/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)
- 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 shivanir@neolytix.com
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