Design a real-time home feed ranker

Q: Design a real-time home feed ranker

This is a ML System Design interview question from Pinterest for Machine Learning Engineer roles. View the full question and solution on PracHub.

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Question

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Scenario

Design a real-time home feed (e.g., social or content platform) that is responsive to user engagement.

Users open the app and see a ranked list of posts/items. As they engage (click/like/comment/dwell), the feed should adapt quickly.

Task

Design the end-to-end system including:

Candidate generation and ranking .
Incorporating real-time engagement signals (both the viewer’s actions and global engagement).
Storage, services, and streaming/infra components needed to meet latency and scale.
Model training, feature pipelines (offline/online), evaluation, and experimentation.

Requirements (state assumptions if needed)

Latency: low p95 end-to-end feed response.
Freshness: newly published items can appear quickly.
Personalization: based on user history + session context.
Reliability: graceful degradation if real-time components fail.
Integrity: prevent spam/manipulation; handle feedback loops.

Design a real-time home feed ranker

Scenario

Task

Requirements (state assumptions if needed)

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