Description
The MLE (Commerce Recommendations) role develops and improves machine learning models for product recommendation in Toss’s commerce domain. Responsibilities include predicting click-through rate, conversion rate, and other user-response metrics; designing recommendation algorithms; conducting experiments, feature engineering, hyperparameter tuning, and offline/online performance analysis; and collaborating with domain experts and data analysts. The role seeks candidates with experience in recommendation systems, prediction-based ranking, and ML model experimentation, with familiarity with PyTorch, TensorFlow, and LightGBM.
