Senior Machine Learning Engineer

Job description

Job Description: Senior Machine Learning Engineer Experience: 6–8 years Employment Type: Full-time Location: Hyderabad Role Summary We are seeking a Senior Machine Learning Engineer to design and build intelligent decision-making systems using time-series forecasting, spatial modeling, and optimization techniques. The role involves evolving systems from rule-based logic to advanced ML and reinforcement learning, and deploying them at production scale. Key Responsibilities ● Build time-series demand forecasting models using rolling statistics, classical ML, and deep learning ● Develop spatial / geospatial models using hexagonal or grid-based representations (e.g., H3) ● Implement classification models (e.g., logistic regression, tree-based models) for risk and state detection ● Design and optimize scoring and ranking engines using weighted heuristics and learned value functions ● Work on policy learning and reinforcement learning for long-horizon optimization ● Own feature engineering, training pipelines, and model evaluation ● Deploy models for batch and near-real-time inference ● Implement model monitoring, drift detection, and retraining workflows ● Collaborate closely with data engineering and backend teams to productionize ML systems Required Skills & Experience ● 7–8 years of hands-on experience in Machine Learning / Applied AI ● Strong proficiency in Python and SQL, FastAPI ● Solid understanding of time-series forecasting techniques ● Experience with classification, regression, and ranking models ● Practical experience with tree-based models (XGBoost, LightGBM, Random Forest) ● Experience designing production ML pipelines ● Strong understanding of feature engineering, model evaluation, and explainability Good to Have ● Experience with spatio-temporal models (ST-GNNs, Transformers, temporal CNNs) ● Exposure to Reinforcement Learning, contextual bandits, or MDP-based systems ● Experience with graph-based modeling ● Familiarity with MLflow, feature stores, Kubernetes ● Experience working with large-scale, high-frequency data systems