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
Robust 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
Robust understanding of feature engineering, model evaluation, and explainability

Valuable 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

📌 Sr Ml Engineer New Delhi (India)
🏢 Walking Tree
📍 India