ML / Recsys Engineer

Join Wildberries as an ML / Recsys Engineer to develop and enhance recommendation algorithms for personalized user experiences.

• •Develop and enhance algorithms that create personalized recommendation feeds on the Wildberries homepage based on user context (action history, time of day, device, seasonality, etc.).
• •Implement and test various ranking strategies from classical (matrix factorization, gradient boosting) to neural network approaches (two-tower models, transformers).
• •Configure specific models and strategies for other marketplace areas and develop media recommendations in Wibes and WB Books.
• •Participate in ranking search results and catalogs, adding personalized signals to algorithms.
• •Develop user profiles and targeting features for quick personalization applications in various scenarios (discount promotions, push notifications, email newsletters).

• •3+ years of experience in ML.
• •Knowledge of classical ML and DL.
• •Understanding of how recommendation systems work.
• •Experience in developing recommendation systems.
• •Strong knowledge of algorithms and data structures.
• •Proficiency in ML stack with Python (Polars, Pandas, Sklearn, Numpy, Scipy, XGBoost/LightGBM/Catboost) and SQL.
• •Experience training models that benefit mass audience products.
• •Knowledge of modern architectures and a desire to develop SOTA approaches to recommendations and ranking (OneRec, HSTU, DCN-v2).
• •Experience deploying models in production.