TL;DR — Search Ranking

Design a search ranking system that uses machine learning to order search results by relevance. The system implements a learning-to-rank pipeline that extracts features from query-document pairs, trains ranking models, and serves predictions at search time with sub-50ms latency. Key features: Feature extraction from query-document pairs. Learning-to-rank model training (pointwise, pairwise, listwise).