Senior Machine Learning Engineer
First seen by Alion on Nov 10, 2026.
Domain : Healthcare Predictive Analytics & Workforce Forecasting
Job 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.
Skills
Machine Learning, Python, Predictive Analytics, Microsoft Fabric, Pandas, Numpy, Time Series Forecasting, Data Science, Statistical Modeling