ML Engineer

Job Overview

This position is responsible for building, training, evaluating, and deploying classical retail ML models for ARIP's most commercially impactful agents. The role involves working with DEAA's MLOps platform and does not require rebuilding open-source software wrappers.

Key Responsibilities

• Build, train, evaluate, and deploy classical retail ML models for W3 agents (A-22..A-25) and W4 Commerce model (A-18..A-21) using DEAA's OSS wrappers (Prophet / DoWhy / EconML / LightFM / scikit-learn / XGBoost)


• Register all models in DEAA's Model Registry (MLflow / Databricks Unity Catalog Models) with model cards; configure drift detection and feature store integration for every governed model


• Run A-22 side-by-side with Oracle Demantra during shadow phase; document Trust Gate progression evidence; prove MAPE ≥5 pts improvement by Wave 3 close


• Build A-25 Causal Insight models (DoWhy / EconML) with mandatory citation patterns and immutable Decision Log; A-25 is read-only — no transactional writes


• Partner with ARIP AI Engineers on model-to-agent integration contracts, latency budgets, fallback behaviour, and HITL gate criteria for ML-heavy agents


• Partner with Suite POs (Songkiat S3, Yaowaluck S1) on BU adoption, gate criteria, and per-model business value documentation

Required Qualifications

• 5+ years building production ML systems in retail / commercial-decisioning: forecasting, replenishment, pricing, or recommendation at multi-store/multi-SKU scale


• Expert in retail forecasting (Prophet / statsmodels / NeuralProphet / DeepAR) and classical ML (XGBoost / LightGBM / scikit-learn)


• Causal inference in production (DoWhy / EconML) — required for A-25 Causal Insight Agent


• MLOps consumer: MLflow / Databricks Unity Catalog Models, Feature Store, drift detection — registers and operates governed models, not builds the platform


• Strong Python + Spark/PySpark; SQL fluency; Databricks (or equivalent lakehouse) production experience


• Calibre: Senior ML Engineer from Agoda (forecasting/pricing), Grab, Shopee, Lazada, Lotus's Australia / Tesco with retail ML production track record