About the company
A product company building an AI-driven supply-chain platform used by large manufacturers, retailers and 3PLs for demand planning, inventory optimisation, transportation and warehouse visibility.
About the role
Build and ship the forecasting and optimisation models at the heart of the product – demand
forecasting, inventory optimisation and lead-time prediction across thousands of SKUs.
What you'll do
Build time-series and ML forecasting models (statistical, gradient boosting, deep learning)
Take models to production with monitoring, retraining and backtesting
Work with customers' planners to translate business problems into models
Improve forecast accuracy and explainability at scale
What we're looking for
3-7 years in applied ML, with production time-series forecasting experience
Strong Python, pandas, scikit-learn/LightGBM; PyTorch a plus
MLOps experience (MLflow, feature stores, model monitoring)
Supply-chain, retail or operations-research background preferred
Why join
Work on a product that runs the day-to-day operations of large enterprise supply chains
Hard, real-world problems: scale, optimisation, messy enterprise data
Strong engineering culture, ownership from design to production
Competitive compensation plus ESOPs; health insurance for family
Key Skills: Python, Time Series Forecasting, scikit-learn, LightGBM, PyTorch, MLOps, SQL
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