01ML System DesignThe complete ML system design interview guide - framework, rubric, and 14 full design problems with model answers.02ML System Design FrameworkA structured 6-step approach to ML system design - requirements, problem formulation, features, model, serving, and evaluation.03Evaluation RubricHow interviewers score ML system design - the rubric behind the grades, with examples of each rating level.04Design: Recommendation SystemDesign a recommendation system - collaborative filtering, content-based, hybrid approaches, cold start, and multi-stage ranking at scale.05Design: Search RankingDesign a search ranking system - query understanding, multi-stage retrieval, learning-to-rank, and personalization.06Design: Fraud DetectionDesign a real-time fraud detection system - extreme class imbalance, feature engineering, low-latency serving, and adversarial evolution.07Design: News Feed RankingDesign a social media feed ranking system - multi-objective optimization, real-time features, diversity, and creator economics.08Design: Ad Click PredictionDesign an ad click prediction system - feature stores, real-time bidding, calibration at scale, and auction mechanics.09Design: Content ModerationDesign an AI content moderation system - multi-modal classification, human-in-the-loop, policy enforcement, and appeals.10Design: Autonomous Driving MLDesign the ML stack for autonomous driving - perception, prediction, planning, safety, and real-time constraints.11Design: AI Chatbot SystemDesign a production AI chatbot - RAG architecture, guardrails, conversation management, evaluation, and cost optimization.12Design: Visual SearchDesign a visual search system - embedding models, approximate nearest neighbors, cross-modal search, and indexing at scale.13Design: Anomaly DetectionDesign an anomaly detection platform - unsupervised methods, streaming detection, alerting, and reducing false alarms.14Design: Machine TranslationDesign a machine translation system - encoder-decoder architecture, quality estimation, low-resource languages, and serving at scale.15Design: Speech RecognitionDesign a speech recognition system - acoustic models, language models, streaming ASR, and real-time transcription.16Design: ML A/B Testing PlatformDesign an A/B testing platform for ML models - experiment tracking, statistical rigor, automation, and guardrail metrics.
