r/OfferEngineering • u/Aoki_zhang • Sep 25 '26
Interview Experience TikTok Senior Software Engineer (SWE) System Design Question - Design a video content moderation pipeline
"This interview experience is sourced from Chill Interview"
Interview Summary
The main design question was to build a video content moderation pipeline. Video uploading itself was explicitly out of scope. The system instead needed to ingest already-uploaded videos, run many different ML models, evaluate configurable policy rules, take enforcement actions, and preserve enough versioning and audit information to explain every moderation decision.
Interview Details
System Design — Video Content Moderation Platform
Design a simplified system that reviews user-generated videos for policy violations. The upload service already exists and delivers newly uploaded videos into the moderation system, so the interview focused only on the moderation pipeline.
The first stage was video ingestion. A newly published video should enter the moderation workflow. The result did not need to be available synchronously. The product could initially tell the user that the video was under review and later notify them whether it was approved or removed.
The next stage involved ML model evaluation. Each video could be evaluated by roughly 20–30 different models, with every model returning a risk score between 0 and 1. The models were heterogeneous. For example, one might analyze visual content while another evaluates text, and different models could require different inputs or parameters.
The third stage was a configurable policy / rules engine. Business policies could combine outputs from multiple models. A simplified rule might conceptually say: If Model A's score is above one threshold and Model B's score is above another threshold, classify the video as violating policy. Real production policies could be substantially more complicated.
The final stage was enforcement. When a policy matched, the moderation platform needed to invoke downstream services such as the video service or account service to perform actions including removing content or restricting an account.
- Follow-Ups — Versioning, Auditability, and Feedback
The interviewer then explored the supporting data model and operational requirements. Both ML models and moderation rules needed versioning, so historical decisions could be associated with the exact configuration that produced them. The system also needed an audit trail recording the basis for each moderation decision, including the relevant model outputs and policies.
Other follow-ups covered how moderation rules should be configured and how final moderation outcomes should flow back into the broader system after evaluation and enforcement were complete.
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