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Experience
Experienced
About the role
Own search quality end to end, covering relevance, ranking, query understanding and the evaluation loop behind them. Frame messy problems into clear problem statements with defined success conditions, and set the quality bar for search. Build working AI-assisted prototypes, including ranking and routing changes tested against real queries, before specs are written. Lead product strategy for the search domain, connecting metric movements to relevance and ranking decisions and making trade-offs explicit. Build and maintain the operations and evaluation layer for search, including eval sets from real queries and LLM-as-judge scoring validated against human labels. Model AI-native practice and help other builders apply AI where it creates real leverage.
Requirements
Strong product judgment with enough technical depth to prototype and reason about search end to end
Has shipped AI-powered features that real users relied on, such as search, recommendations, ranking or conversational interfaces
Hands-on with evaluation pipelines, ideally LLM-as-judge, and familiar with hybrid retrieval and intent classification
Uses AI as a primary co-worker across daily workflow and validates outputs against own judgment
Independently strategic and able to make the right call in ambiguous, cross-functional situations
Can point to a consumer metric that moved because of a search decision they owned
Benefits
Career growth opportunities
Competitive compensation based on performance
Candid, open and collaborative culture
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