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

Himalayas, a remote job marketplace with more than 100,000 listings and 300,000 public talent profiles, adopted Qdrant Cloud in 2023 to improve matching across varied job descriptions, candidate backgrounds, and practical employment constraints. After finding Algolia and Elasticsearch costly at scale and limited by keyword-based retrieval, the company sought a system that could combine semantic understanding with exact keyword matches and filters for factors such as location, time-zone overlap, work authorization, and employment type. Its production pipeline uses Qdrant for hybrid retrieval and payload filtering, while Himalayas ranks and presents results for search, personalized recommendations, and related-job suggestions. Qdrant now supports hundreds of thousands of daily requests across roughly 3 million data points, with median retrieval latency near 30 milliseconds, and recent search improvements reportedly raised recall by about 19 percentage points while reducing irrelevant results by roughly fourfold. Himalayas plans to further use AI-driven evaluation to continuously measure and improve how well job results and recommendations fit users’ queries and profiles.

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