Mid-level interview questionAsked at TikTok · interview write-up
In the recall stage of a recommender, design a model that chooses how many candidates K to retrieve per request given latency and compute cost.
Model answer
Predict the marginal value of more candidates per request. Label offline by replaying traffic at several K values and recording where the final ranker's top results stop changing.
Features: user activity, history length, request context and current load. A small model, say gradient-boosted trees, picks K from a few buckets to maximise value minus latency and compute cost, with a safe floor. A/B test against fixed K, watching p99 latency.
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