Artificial Intelligence Engineer

Role : AI Engineer

Location: Hyderabad

Exp: 5-10 Years

Mode: 5 Days ( WFO)

Interview : 2nd round F2F.

Ready to work either Morning or Mid shifts...

Why This Role Matters

AI in healthcare RCM is transformative. Your ML models can predict claim denials before submission, detect fraudulent patterns, accelerate payment recovery, and unlock insights hidden in millions of healthcare transactions. Unlike traditional features, ML systems compound in valuethey improve continuously, adapt to market changes, and deliver exponential ROI over time.

Key Responsibilities

• Design and implement ML models for healthcare revenue cycle applications (claim prediction, anomaly detection, outcome forecasting)
• Develop NLP solutions for healthcare document analysis, claim interpretation, and compliance classification
• Engineer production-grade ML pipelines with versioning, retraining, and A/B testing capabilities
• Implement MLOps practices including model monitoring, performance tracking, and automated retraining
• Work with large healthcare datasets, ensuring proper data preprocessing, feature engineering, and handling of missing/imbalanced data
• Collaborate with data scientists to translate research into production implementations
• Implement healthcare-compliant data pipelines that maintain HIPAA privacy and security standards
• Monitor model performance in production, diagnose drift, and implement remediation strategies
• Document model architecture, training procedures, and deployment runbooks for operational teams
• Stay current with ML research and emerging healthcare AI applications, proposing innovations to the product roadmap

Required Qualifications

• 5+ years of professional machine learning engineering experience with demonstrated production ML systems
• Advanced Python proficiency for ML development, data manipulation, and experimentation
• Strong SQL skills for large-scale data extraction and feature engineering
• Hands-on experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Demonstrated expertise in MLOps practices (model versioning, monitoring, retraining pipelines)
• Experience with NLP and document analysis techniques
• Understanding of healthcare compliance requirements (HIPAA, SOC 2, FDA guidelines for software)
• Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent advanced professional experience

Preferred Qualifications

• Healthcare domain expertise or experience applying ML in healthcare settings
• RCM industry knowledge or familiarity with healthcare claim processing
• Experience with cloud ML platforms (AWS SageMaker, Azure ML, GCP Vertex AI)
• Knowledge of responsible AI practices, model explainability, and bias mitigation
• Published research or contributions to ML open-source projects
• Experience with advanced NLP models (BERT, transformers, Large Language Models)