Sr ML Engineer

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+ 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 systemsRole & responsibilities