Top 35
Prep plan
Updated weekly · Last refresh Aug 30

Nextdoor Machine Learning Engineer Interview Questions

The questions to prepare for a Nextdoor Machine Learning Engineer interview. Questions from real interview reports rank first. Updated weekly.

35questions
~5htotal time
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1
CodingStart here. 5 questions · ~42 min
Directed Graph Cycle DetectionMedium
Practice

Determine whether a directed graph contains a cycle using DFS or topological sorting.

RecursionGraphsNextdoor
In-Memory Feed Preference CacheHard

Tests data structure design and careful implementation for caching personalized Nextdoor feed preferences.

RecursionHash TablesData StructuresNextdoor
Two-Pointer Pattern SearchMedium

Tests algorithmic thinking and efficient two-pointer techniques on structured rating data.

ArraysAlgorithmsTwo PointersNextdoor
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2
System Design9 questions · ~76 min
Cold Start for New NeighborhoodsHard

Tests strategies for bootstrapping recommendations and models with no prior data.

Cold StartFeature DriftRecommendation SystemsNextdoor
Collaborative vs Content Filtering for AdsMedium

Tests understanding of recommender approaches and how to choose for ad targeting use cases.

Feature EngineeringRecommendation SystemsNextdoor
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3
Behavioral & Leadership18 questions · ~153 min
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4
More topics3 questions · ~25 min
NLP Topic Classification for PostsMedium

Tests NLP pipeline design for multi-topic classification of real user-generated neighborhood content.

Text ClassificationNLPTokenizationNextdoor
Production Model MaintenanceMedium

Evaluates your MLOps practices for monitoring, retraining, and managing model drift and quality.

productionNextdoor
Precision-Recall and BaggingMedium

Assesses your understanding of evaluation metrics and ensemble methods in machine learning.

Nextdoor
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