How Himalayas Built Semantic Job Matching for 100,000+ Remote Listings with Qdrant - Qdrant

This post details how Himalayas uses Qdrant's hybrid search and payload filtering to build a semantic job matching system for over 100,000 listings. It highlights the trade-offs of keyword search (Algolia, Elasticsearch) versus semantic search with Qdrant, emphasizing the need for both semantic similarity and precise filters (location, time zone, employment type) within a single query. The architecture combines semantic and keyword retrieval with payload filters, with Qdrant handling retrieval and filtering, and the Himalayas application handling final ranking and presentation. The post also mentions recent improvements that increased recall by 19 percentage points and cut irrelevant results by 4x.