{"id":4016562,"url":"https://alion.io/job/mouri-tech-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":3800648,"name":"MOURI Tech","domain":"mouritech.com","url":"https://alion.io/company/mouri-tech","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India","Bengaluru, India","Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Microsoft Fabric","optional":false},{"name":"NumPy","optional":false},{"name":"Pandas","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SHAP","optional":false},{"name":"SQL","optional":false},{"name":"Time Series","optional":false},{"name":"XGBoost","optional":false}],"status":"live","first_seen_at":"2026-11-10T12:19:10Z","employer_posted_date":null,"last_verified_at":"2026-11-10T12:19:10Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Domain : Healthcare Predictive Analytics & Workforce Forecasting\n\nJob Overview :\n\nWe 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.\n\nCandidates should have hands-on experience with Microsoft Fabric Lakehouse and production-grade ML pipelines.\n\nKey Responsibilities :\n\n- Perform data exploration, cleaning, preprocessing, and feature engineering.\n\n- Develop and deploy ML models for classification, prediction, and time-series forecasting.\n\n- Build predictive models using XGBoost, Random Forest, and Scikit-learn.\n\n- Implement model explainability using SHAP.\n\n- Develop end-to-end ML pipelines covering training, validation, scoring, and deployment.\n\n- Work with Microsoft Fabric Lakehouse, notebooks, and data pipelines.\n\n- Monitor model performance, data quality, drift, and implement retraining processes.\n\n- Integrate ML outputs with APIs and Power BI dashboards.\n\n- Collaborate with Data Engineers, Architects, and BI teams.\n\nRequired Technical Skills :\n\n- Strong Python, Pandas, NumPy, and SQL skills.\n\n- Hands-on experience with Scikit-learn, XGBoost, Random Forest, and statistical modelling.\n\n- Experience in classification, predictive analytics, and time-series forecasting.\n\n- Strong knowledge of EDA, feature engineering, model evaluation, and hyperparameter tuning.\n\n- Experience with SHAP and model explainability.\n\n- Hands-on experience with Microsoft Fabric, Fabric Lakehouse, notebooks, and data pipelines.\n\n- Experience in ML model deployment, monitoring, versioning, and retraining.\n\n- Knowledge of MLOps practices and Power BI/API integration.\n\nCandidate Expectations :\n\n- 8 years of relevant AI/ML or Data Science experience.\n\n- Proven experience developing and deploying end-to-end ML solutions.\n\n- Ability to independently handle data preparation, model development, deployment, and monitoring.\n\n- Strong analytical, problem-solving, and communication skills.\n\n- Important: Practical ML model development and deployment experience is mandatory.\n\n- Candidates must have hands-on exposure to Microsoft Fabric Lakehouse and working with Lakehouse data.\n\n- Theoretical ML knowledge or data engineering-only experience will not be 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