k-NN is quick to code and a solid check of vectorization and the lazy-learner tradeoff. Interviewers look for a tidy vectorized distance calculation plus knowing why naive prediction is O(n) and how to accelerate it. The implementation follows.
Updated Sep 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.
k-NN is quick to code and a solid check of vectorization and the lazy-learner tradeoff. Interviewers look for a tidy vectorized distance calculation plus knowing why naive prediction is O(n) and how to accelerate it. The implementation follows.
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