Google ML & AI interview questions.
Questions in the CrackML corpus associated with Google. Use company evidence as a prioritization signal, not a promise that an exact question will repeat.
Design a content moderation ML systemML System Design · hard · Evidence 77/100Design an ML system using traffic dataML System Design · hard · Evidence 77/100Logger Timer With Additional ConstraintsPython & DSA · medium · Evidence 77/100Optimize a Grid Computation From O(n²) to O(n)Python & DSA · hard · Evidence 77/100Design a Traffic-Data ML SystemML System Design · hard · Evidence 77/100Design a system to detect copyright violations on YouTubeML System Design · hard · Evidence 75/100Design a small polite LLM that runs on a phoneGenAI & LLM · hard · Evidence 75/100Why use RAG instead of fine-tuning an LLM?GenAI & LLM · medium · Evidence 66/100Implement a Categorical SamplerML Coding & PyTorch · medium · Evidence 66/100Efficient Multinomial SamplingML Math · medium · Evidence 66/100Design a Q&A BotML System Design · hard · Evidence 41/100How would you design fallback behavior when a Q&A bot cannot retrieve enough evidence?GenAI & LLM · hard · Evidence 41/100Design a Places Recommendation System for MapsML System Design · hard · Evidence 41/100How would you evaluate retrieval quality separately from answer quality in a Q&A bot?GenAI & LLM · hard · Evidence 41/100For a Q&A bot, when would you add RAG instead of relying on a parametric model alone?GenAI & LLM · medium · Evidence 41/100Why can the same algorithm produce different success rates on the same dataset?ML Fundamentals · medium · Evidence 31/100Explain precision vs recall and when each mattersML Fundamentals · medium · Evidence 31/100