Requirements Proficiency in Python and PySpark for data analysis, machine learning, and demand forecasting (regression + time series models) Experience with forecasting models such as LightGBM/ XGBoost and classical time series methods (e.g., ETS/ARIMA) Strong understanding of
Company Description An enterprise client is currently recruiting people who can bring energy, emotion, and clarity to their voice, whether you’re a professional actor or someone with a naturally expressive personality. This is part of a
The Senior ML Engineer (MLOps) owns the transition from ad-hoc ML deployments to a registered, monitored, governed ML platform — the lifecycle every data scientist and ML practitioner across the company uses. The role also curates
Requirements Proficiency in Python and PySpark for data analysis, machine learning, and demand forecasting (regression + time series models) Experience with forecasting models such as LightGBM/ XGBoost and classical time series methods (e.g., ETS/ARIMA) Strong understanding of
The AI Engineer builds production agents end-to-end on an AI-native retail decisioning platform — prompt design, tool definitions, multi-step workflows on the agent runtime (LangGraph, CrewAI, or chosen framework), evaluation harnesses (golden sets, regression gates, multi-step
The Head of Retail AI Platform is the senior leader accountable for an AI-native retail decisioning platform end-to-end — strategy, roadmap, delivery, team, governance, and commercial outcome. The platform delivers a portfolio of product suites and
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,