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Tree traversal questions were mostly LeetCode medium level, focusing on classic BFS and DFS patterns without heavy backtracking. The emphasis was on implementing standard traversals cleanly, understanding when to use iterative vs recursive approaches, and handling common variations like level-order processing or simple tree properties.
The ML and system design portion focused primarily on recommender systems, along with fundamental machine learning theory. This included discussing how to design a recommendation pipeline end-to-end, tradeoffs between different approaches, and demonstrating a solid grasp of core concepts like model evaluation, overfitting, and basic algorithms.
Altre recensioni di colloqui per Machine Learning Engineer presso Nextdoor
Ho presentato la mia candidatura online. Ho sostenuto un colloquio presso Nextdoor nel mese di mag 2026
Colloquio
first is hr call 30 mins, then 1h general coding and 1h ml coding, if passing, there will be another 1.5h interview for genereal coding and hebavior question. The hr call is mainly for introducing the interview process and checking interest,
Round 1: Backend Coding(1h) + ML coding(1h)
Backend Coding: A non-leetcode question with regard to hashmap and recursion
ML coding: Given a dataset, build a pipeline from data preprocessing to model training to evaluation
