Google Applied Scientist Interview Questions
The questions to prepare for a Google Applied Scientist interview. Questions from real interview reports rank first. Updated weekly.
Rebuild a binary tree from preorder and inorder traversals using recursion and an index map in O(n) time.
GoogleCompute AUROC from binary labels and predicted probabilities by sorting scores and integrating the ROC curve.
GoogleExplain vanishing gradients in deep networks and how residual connections, batch normalization, and activation choice improve training.
GoogleHandle severe class imbalance in a binary deep learning model using sampling, weighted losses, and the right evaluation metrics.
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Design a short-video recommendation system that balances immediate engagement with long-term retention in a personalized feed.
GoogleDesign a deep learning based query autocomplete system with real-time retrieval, ranking, training pipelines, and low-latency serving.
GoogleExplain the Central Limit Theorem, its assumptions, and when normal approximations break down in practice.
GoogleExplain how transformer self-attention works, including its role in sequence modeling and why it scales better than RNNs.
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