Build forecasting systems.
Design, implement, and continuously improve time-series models for demand, sales, and other ecommerce KPIs.
Develop AI-driven insights.
Build generative AI workflows that interpret data and produce clear, useful summaries and recommendations for users.
Own production ML systems (MLOps).
Design and maintain pipelines for training, evaluation, deployment, and monitoring to ensure models remain accurate as data and market conditions evolve.
Implement context-aware AI (RAG).
Collaborate on data foundations.

Deep experience building and deploying production-grade ML systems (e.g. forecasting, regression, recommendation systems).
Strong Python and experience in the modern ML ecosystem (Pandas, Scikit-learn, PyTorch or similar).
Hands-on experience working with LLM-based systems including prompting, orchestration, APIs and evaluation.
Experience productionising ML systems (model lifecycle, monitoring, retraining, performance trade-offs).
Solid data engineering fundamentals.
Ability to make pragmatic technical decisions in a product engineering environment, balancing experimentation with reliability.

Senior Machine Learning Engineer – Product

Key skills