Scalable Content Moderation System

Multimodal Firearm Detection System

Design a high-scale trust and safety system to detect firearm listings on a global marketplace. The system must process multimodal data (text and images) at the point of upload. Your design should address high-throughput data ingestion, low-latency multimodal inference (P99 < 500ms), strategies for handling extreme class imbalance and adversarial evasion, and a robust feedback loop for human-in-the-loop moderation and model retraining.
CLIPDistilBERTPyTorchKafkaSparkTriton Inference ServerRedisPerceptual HashingActive Learning
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Scalable Toxic Content Detection System

Design an end-to-end toxic content detection system for a high-traffic social media platform (1B+ posts/day). The system must handle real-time automated moderation with low latency (<150ms) while minimizing false positives to protect user expression. Your design should detail the data ingestion strategy, the model architecture for semantic understanding, techniques for handling adversarial text, and a robust evaluation framework that incorporates human-in-the-loop feedback and fairness auditing.
DistilBERTTransformersONNXTensorRTKafkaFlinkSparkRedisTritonMLflowGreat Expectations
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Scalable Misinformation & Fake News Detection System

Design a high-throughput system to detect and mitigate the spread of fake news on a global social media platform. Your design should address: 1) Handling 100k+ QPS with low-latency constraints, 2) Mitigating extreme class imbalance and adversarial content evasion, 3) Integrating human-in-the-loop feedback with automated retraining, 4) Defining multi-stage model architectures that balance computational cost with classification accuracy, and 5) Ensuring system reliability and explainability for moderation decisions.
DistilBERTXGBoostTransformersKafkaFlinkSparkTectonTriton Inference ServerTensorRTSHAPCLIP
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Scalable Content Moderation System

Design a high-scale content moderation system for a global social media platform. The system must process 100M+ text and image uploads per day with a P99 latency of under 200ms. Your design should cover the end-to-end ML lifecycle, including fast-path filtering, multi-modal scoring models, human-in-the-loop workflows for active learning, and strategies for handling adversarial content and data drift. Address how you would balance precision and recall while managing the costs of inference and human review.
DistilBERTResNetLightGBMONNXTensorRTKafkaRedisPerceptual HashingActive LearningOCR
00
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