Senior Machine Learning Engineer

As a Machine Learning Engineer at TRIARQ Health, you will play a crucial role in leading the development and deployment of cutting-edge ML models that drive intelligent products and insights. Your expertise will be instrumental in collaborating with cross-functional teams in Data Science, Engineering, and Product to create scalable, efficient, and impactful solutions. While prior exposure to the healthcare domain is advantageous, it is not a mandatory requirement for this role. Key Responsibilities: - Design, construct, and manage end-to-end ML systems, encompassing data pipelines through to model deployment. - Develop and enhance machine learning models for various applications such as classification, prediction, recommendation, NLP, and computer vision. - Implement best MLOps practices for model training, tracking, deployment, and monitoring to ensure operational efficiency. - Work closely with data scientists and subject matter experts to transition prototypes and research into production-ready solutions. - Evaluate and oversee model performance to guarantee robustness, fairness, and interpretability. - Document system architecture and processes, actively participate in knowledge sharing, and engage in code reviews. - (Preferred) Engage with EHR data, claims data, clinical notes, or healthcare interoperability standards like HL7 or FHIR, as appropriate. Required Skills & Qualifications: - Hold a Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field. - Possess over 5 years of practical experience in ML engineering or applied data science. - Proficient in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, and XGBoost. - Demonstrated experience in deploying ML models in production utilizing containerization (e.g., Docker, Kubernetes) and cloud platforms (AWS/GCP/Azure). - Familiarity with MLOps tools like MLflow, DVC, or Kubeflow. - Skilled in constructing ETL/ELT pipelines and managing large-scale datasets effectively. - Strong grasp of statistical methods, model evaluation metrics, and optimization techniques. - Proficiency in software engineering practices including version control, testing, and CI/CD. Preferred Qualifications: - Exposure to healthcare datasets like medical claims, EHR/EMR, HL7, FHIR, or medical coding (CPT, ICD-10). - Experience with NLP models applied to clinical documentation or unstructured medical data. - Understanding of HIPAA compliance, data anonymization, and PHI handling. - Contributions to open-source ML projects or peer-reviewed publications. - Previous work experience in regulated industries or mission-critical settings. Location: Nashik, Pune, Navi Mumbai Department: AI & ML Engineering Experience Level: 5+ years,