314,552 interview questions from 6,000+ companies.
Design a production ranking system with robust feature drift monitoring across batch and real-time features at high QPS.
Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.
Design a shared feature store for training and low-latency inference across many ML systems with strict freshness and consistency needs.
Design an end-to-end product recommendation system for a large e-commerce marketplace with strict latency and freshness needs.
Design a personalized recommendation system that turns user preferences into ranked suggestions with retrieval, ranking, and feedback loops.
Design a distributed ML serving platform that stays available and scales under failures, traffic spikes, and model updates.
Design a URL shortening service that routes, ranks, and monitors links at scale.
Design a cloud ML deployment system for a security product, covering training, serving, updates, and production monitoring.
Design a recommendation system strategy for model cold start and new-user cold start, including serving, evaluation, and safe rollout.
Design a recommendation system strategy for new users and new items when interaction history is sparse or missing.
Design a production deployment path for a personalized ranking model, with serving, feature consistency, drift handling, and experiment driven rollout.
Design a URL shortener that ranks and recommends short links while handling abuse, freshness, and monitoring at scale.
Design a recommendation and ranking system that handles cold start for both new users and new items without hurting feed quality.
Design a production ML decision service with low latency serving, secure data handling, and scalable training and inference.
Design a production ML deployment on Google Cloud with serving, feature management, rollout, monitoring, and evaluation.
Design the ML system behind a real-time chat app, including message ranking, retrieval, serving, and feedback loops.
Design a low latency ML inference platform for high-frequency online predictions with strict response times and evolving model features.
Design an end-to-end travel recommendation system with retrieval, ranking, feature pipelines, and online feedback loops.
Design a personalized feed ranking system that handles new users and new content under tight latency at large scale.
Design a real-time fraud scoring system for card transactions with strict latency, delayed labels, and high availability requirements.
4,676 total questions
