The ML Engineer builds the classical retail-ML cores that power the highest-stakes agents on an AI-native retail decisioning platform — demand forecasting that must beat a legacy system, replenishment and allocation models, causal-insight models for executive narratives, and pricing / promotion / markdown / assortment models. The role consumes the enterprise MLOps platform (model registry, drift detection, feature store, library wrappers) and contributes use-case-specific implementations. 

Remote candidates outside of Thailand are welcome to apply.

Key Responsibilities:

• Build, train, evaluate, and deploy classical retail ML models — forecasting, replenishment, allocation, causal inference (DoWhy / EconML), pricing elasticity, promotion lift, markdown optimisation, assortment. 
• Use company-curated classical ML wrappers (Prophet, statsmodels, ...