System designHardsd-g346

Subject RankingLevel Senior–Staff~50 minCommon in ML systems interviewsIndustries Technology

Question

Design the logging and offline-evaluation infrastructure that lets a ranking team estimate 'how would a new ranker have performed?' *without* shipping it to live traffic for every candidate model. The hard problem: your logs only contain feedback (clicks/conversions) on items the *current* ranker chose to show — you have no labels for items it didn't show, and clicks are heavily position-biased (top results get clicked regardless of relevance). How do you log and evaluate so offline estimates predict online results?

What a strong answer looks like

Clarify scale and constraints first. Propose a clean component breakdown, then go deep on the hard parts — data model, bottlenecks, consistency, failure modes — and name the trade-offs you are making.

Learn the concepts

Narrate your design

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