Content moderation pipeline
Design a content-moderation ML pipeline for a platform ingesting 50M pieces of user content/day (text, images, video) that must detect policy violations (hate, violence, CSAM, spam) with both proactive (pre-publish) and reactive (post-report) paths. Pre-publish scoring for text/images must complete within 300ms; video can be asynchronous. Cover the model architecture, the human-review loop, and how you trade off catching harm against over-removal.
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.
Clarify6:00 left
Estimate6:00 planned
Design18:30 planned
Deep dive14:30 planned
Failure10:00 planned
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.