Google Coding & Algorithms Interview Questions
Practice 461 real Google interview questions for 2026 — Google interview questions that cover Coding & Algorithms, Behavioral & Leadership, Analytics & Experimentation, Machine Learning, and Statistics & Math across Software Engineer, Data Scientist, Machine Learning Engineer, and Product Manager roles. Real questions from actual interviews with detailed solutions tailored for interview preparation and role-specific skill building. Expect coding-heavy rounds and design-focused conversations first, then analytics and behavioral assessments that probe impact, collaboration, and "Googleyness." For Software Engineer candidates this collection emphasizes string and substring matching, memory-efficient undo/redo and batched state operations, graph/time-series connectivity and queue problems, plus scaling for huge inputs and behavioral scenarios about teamwork and ambiguity. Data Scientist questions repeat themes in causal and unbiased upgrade experiments, bootstrap inference and percentile estimation from buckets, sampling and subarray algorithms, and sequence analytics. Machine Learning Engineer prompts focus on LLM lifecycle and trade-offs, recommendation and cold-start ranking strategies, weighted sampling and search, and building chatbots over mixed structured/unstructured data. Product Manager items center on Google Maps/Android product ideation, real-time data throughput and estimation, market sizing, and explaining technical tradeoffs to non-technical stakeholders. Use targeted coding practice, mock design interviews, experiment design drills, and concise STAR stories for best results.
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