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Updated weekly · Last refresh Aug 30

Scribd Machine Learning Engineer Interview Questions

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

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1
CodingStart here. 28 questions · ~349 min
Maximum Depth of Binary TreeEasy
Practice

Problem Given the root of a binary tree, return its maximum depth as an integer. The maximum depth is the number of nodes along the longest path from the ...

RecursionQueueTreesScribd
Count Vowels in a StringEasy
Practice

Implement a function to count the number of vowels in a given string.

StringsScribd
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2
Machine Learning13 questions · ~162 min
Handling Missing Values in MLEasy

Explain practical strategies for handling missing values in a supervised learning workflow, from diagnosis to modeling and validation.

Cross-ValidationFeature EngineeringRegularizationScribd
Improve Loan Default Prediction FeaturesEasy

Build and compare baseline and engineered-feature classifiers for consumer loan default prediction, and explain how feature engineering changes model performance.

Cross-ValidationFeature EngineeringSupervised LearningScribd
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3
Model Evaluation4 questions · ~50 min
Assess Offline NDCG Impact on User Reading TimeMedium

Evaluate whether a 5% increase in NDCG correlates with a rise in user reading time for a content recommendation system.

PrecisionAccuracyRecallScribd
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4
Pipelines3 questions · ~37 min
Feature Store for Batch vs StreamingHard

Assesses system design for reliable feature generation, consistency, and low-latency serving.

ETLOrchestrationData ModelingScribd
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5
More topics2 questions · ~25 min
Explain TF-IDF for Text FeaturesEasy

Explain TF-IDF and where it helps in text classification and search.

Text ClassificationTF-IDFTokenizationScribd
Central Limit Theorem ImportanceEasy

Tests understanding of sampling distributions and their impact on inference.

DistributionsCentral Limit TheoremExpected ValueScribd
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