Applied Research Interview Questions

102 applied research interview questions shared by candidates

First 10 minutes were spent discussing the team's background, goals, and current projects. Then 3- minutes for questions pertaining to my technical background and prior projects that overlapped with the work their team was doing. Remaining 5 minutes for Q&A.
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Applied Deep Learning Research

Interviewed at NVIDIA

4.4
Aug 16, 2023

First 10 minutes were spent discussing the team's background, goals, and current projects. Then 3- minutes for questions pertaining to my technical background and prior projects that overlapped with the work their team was doing. Remaining 5 minutes for Q&A.

Problem: Top K Most Similar Documents You are given: an integer array queryEmb of length D, representing a query embedding a 2D integer array docEmbs of size N x D, representing N document embeddings an integer k All embeddings are already L2-normalized. The cosine similarity between two normalized vectors is equal to their dot product. Return the indices of the k documents with the highest cosine similarity to queryEmb, ordered from most similar to least similar. If k > N, return all document indices sorted by similarity. Function Signature def topKSimilar(queryEmb: np.ndarray, docEmbs: np.ndarray, k: int) -> np.ndarray
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Applied Research Scientist

Interviewed at Microsoft

4
Mar 21, 2026

Problem: Top K Most Similar Documents You are given: an integer array queryEmb of length D, representing a query embedding a 2D integer array docEmbs of size N x D, representing N document embeddings an integer k All embeddings are already L2-normalized. The cosine similarity between two normalized vectors is equal to their dot product. Return the indices of the k documents with the highest cosine similarity to queryEmb, ordered from most similar to least similar. If k > N, return all document indices sorted by similarity. Function Signature def topKSimilar(queryEmb: np.ndarray, docEmbs: np.ndarray, k: int) -> np.ndarray

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