Senior Machine Learning Engineer

Domain : Healthcare Predictive Analytics & Workforce ForecastingJob Overview :We are looking for experienced Machine Learning Engineers with strong expertise in Python, Machine Learning, Predictive Analytics, and Forecasting to develop and deploy end-to-end ML solutions.Candidates should have hands-on experience with Microsoft Fabric Lakehouse and production-grade ML pipelines.Key Responsibilities :- Perform data exploration, cleaning, preprocessing, and feature engineering.- Develop and deploy ML models for classification, prediction, and time-series forecasting.- Build predictive models using XGBoost, Random Forest, and Scikit-learn.- Implement model explainability using SHAP.- Develop end-to-end ML pipelines covering training, validation, scoring, and deployment.- Work with Microsoft Fabric Lakehouse, notebooks, and data pipelines.- Monitor model performance, data quality, drift, and implement retraining processes.- Integrate ML outputs with APIs and Power BI dashboards.- Collaborate with Data Engineers, Architects, and BI teams.Required Technical Skills :- Strong Python, Pandas, NumPy, and SQL skills.- Hands-on experience with Scikit-learn, XGBoost, Random Forest, and statistical modelling.- Experience in classification, predictive analytics, and time-series forecasting.- Strong knowledge of EDA, feature engineering, model evaluation, and hyperparameter tuning.- Experience with SHAP and model explainability.- Hands-on experience with Microsoft Fabric, Fabric Lakehouse, notebooks, and data pipelines.- Experience in ML model deployment, monitoring, versioning, and retraining.- Knowledge of MLOps practices and Power BI/API integration.Candidate Expectations :- 8 years of relevant AI/ML or Data Science experience.- Proven experience developing and deploying end-to-end ML solutions.- Ability to independently handle data preparation, model development, deployment, and monitoring.- Strong analytical, problem-solving, and communication skills.- Important: Practical ML model development and deployment experience is mandatory.- Candidates must have hands-on exposure to Microsoft Fabric Lakehouse and working with Lakehouse data.- Theoretical ML knowledge or data engineering-only experience will not be sufficient. (ref:hirist.tech)