Overview

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.

Responsibilities

• Build time-series demand forecasting models using rolling statistics, classical ML, and
• Develop spatial / geospatial models using hexagonal or grid-based representations
• Implement classification models (e.g., logistic regression, tree-based models) for risk
• Design and optimize scoring and ranking engines using weighted heuristics and
• 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

Qualifications

• 7+ years of hands-on experience in Machine Learning / Applied AI
• Strong proficiency in Python and SQL, FastAPI
• Solid understanding of time-series forecasting techniques
• Practical experience with tree-based models (XGBoost, LightGBM, Random Forest)
• Strong understanding of feature engineering, model evaluation, and explainability
• Exposure to Reinforcement Learning, contextual bandits, or MDP-based systems
• Familiarity with MLflow, feature stores, Kubernetes