Google Interview Questions

Practice 514 real Google interview questions for 2026. Covers Coding & Algorithms, Behavioral & Leadership, Analytics & Experimentation, Machine Learning, and System Design across Software Engineer, Data Scientist, Machine Learning Engineer, Product Manager, and Data Engineer roles — real questions from actual interviews with detailed solutions to accelerate interview preparation. This collection highlights the coding-first bar Google uses: expect heavy algorithmic work, role-related data and ML problems, a Googleyness/leadership round, and level-specific differences in what’s decisive. What’s distinctive: for Software Engineers you’ll see spatial and streaming algorithms, concurrency and async primitives, LLM-foundations and GPU-job scheduling, plus object-design problems like room assignment; Data Scientists are weighted toward causal experiments, funnel and product-metric diagnostics, bootstrap inference, and percentile/sampling algorithms; ML Engineers focus on transformer blocks, recommendation design and ranking cold-starts; PMs get Maps/Android and product-ideation tradeoffs plus throughput and revenue sizing. New-grad and intern tracks emphasize phone screens and virtual onsites; Google L4 typically keeps the loop coding-heavy while Google L5 expects stronger system-design and cross-team leadership signals. Use focused practice, mock interviews, and level-specific stories to prepare.