Design a harmful-content detection system for a Twitter-scale social platform. Every newly created post must be evaluated at publish time before it reaches a meaningful audience. In v1, posts contain text and images; video and live content are out of scope.
The ML task is multimodal, multi-label classification. Given a post's text, image, and lightweight author and reach context, the system should predict a calibrated…
