Machine Learning Intern

1 Month ago • All levels • Research Development

Job Summary

Job Description

Neolytix is seeking an experienced MLOps Engineer for their US Healthcare Claims Management platform. The role involves building, deploying, and maintaining AI/ML systems for analyzing claims, prioritizing denials, and optimizing revenue recovery. Key responsibilities include designing ML pipelines, deploying LLMs and SLMs using containerization and Azure, implementing monitoring systems, establishing CI/CD for ML, engineering data pipelines for healthcare claims data, optimizing models, and documenting technical solutions. The ideal candidate will have experience operationalizing LLMs in enterprise applications and a background in healthcare technology or revenue cycle operations.
Must have:
  • Proficiency in Python with OOP
  • Experience developing APIs (Flask/FastAPI)
  • Expertise in version control (GitHub/GitLab)
  • Proficiency in SQL, NoSQL, and vector databases
  • Experience with Azure cloud services
  • Familiarity with PyTorch/TensorFlow/Hugging Face
Good to have:
  • Experience operationalizing LLMs for enterprise applications
  • Background in healthcare technology or revenue cycle operations
  • Track record of improving production model performance
Perks:
  • Competitive salary and benefits package
  • Opportunity to contribute to AI solutions in healthcare
  • Dynamic and collaborative work environment
  • Opportunities for continuous learning and professional growth

Job Details

Job Description: Machine Learning Engineer - US Healthcare Claims Management 

Position: MLOps Engineer - US Healthcare Claims Management 
Location: Gurgaon, Delhi NCR, India 
Company: Neolytix 

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 on operationalizing 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 - 

  • Experience developing APIs using Flask or Fast API frameworks –   

  • Integration knowledge with front-end applications –

  • Expertise in version control systems (e.g., GitHub, GitLab, Azure DevOps) - 

  • Proficiency in databases, including SQL, NoSQL and vector databases –   

  • Experience with Azure

  • 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. 

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 vidya@neolytix.com 

 

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