Design a weapon-sale ad detection system

Q: Design a weapon-sale ad detection system

This question evaluates a candidate's competence in end-to-end machine learning system design, covering multimodal signal integration (text, images, behavior), data collection and labeling strategies, model evaluation and monitoring, and operational enforcement workflows for policy-violating content.

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ML System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master ml system design interviews.

Question

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Design an end-to-end ML system to detect and take action on ads/listings that attempt to sell weapons (or weapon-related prohibited items).

Your system should cover:

Where detection happens (at creation time vs post-publication)
What signals/modalities you use (text, images, seller behavior, etc.)
How you collect and label training data
How you evaluate and monitor the model
How you integrate with enforcement (block, downrank, human review)

The interviewer may also ask:

How would you collect training data, especially for rare policy-violating content?
In a “funnel” setting (impression → click → conversion), is the training data the same for each stage/model? Why or why not?

Design a weapon-sale ad detection system

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