Senior Machine Learning Engineer

• 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 (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 optimisation
• 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

• 5-7 years of hands-on experience in Machine Learning / Applied AI
• Strong proficiency in Python, SQL, and 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, and Kubernetes
• Experience working with large-scale, high-frequency data systems