Senior interview questionAsked at DoorDash · interview write-up
Design a low-latency store recommender for a delivery app's homepage, covering retrieval, pre-ranking, ranking, geospatial caching and feature serving.
Model answer
A cascade, cheap to expensive. Retrieval: stores that deliver to the user's location, from a geohash index, merged with two-tower candidates and popular-nearby lists. Pre-ranking trims them with a light model. Ranking runs a richer multi-task model over user, store and context features.
Cache store lists and slow-changing features per geohash cell; ETA and store busyness come from a low-latency feature store. Give each stage a latency budget with timeouts, and fall back to the cached popular list.
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