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Updated weekly · Last refresh Aug 30

phData Machine Learning Engineer Interview Questions

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

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1
Machine LearningStart here. 4 questions · ~36 min
Supervised vs Unsupervised LearningEasy

Explain how supervised and unsupervised learning differ, and ground the distinction in a practical ML example.

Unsupervised LearningFeature EngineeringBias-Variance TradeoffphData
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 EngineeringRegularizationphData
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2
System Design3 questions · ~27 min
Deploy a Cloud ML Inference SystemMedium

Design a cloud ML deployment system for a security product, covering training, serving, updates, and production monitoring.

InfrastructureFeature DriftModel ServingphData
Design a Personalized Product RecommenderHard

Design an end-to-end product recommendation system for a large e-commerce marketplace with strict latency and freshness needs.

Feature StoreFeature DriftModel ServingphData
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3
Behavioral & Leadership6 questions · ~54 min
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4
More topics4 questions · ~36 min
KNN From ScratchHard
Practice

Implement K-nearest neighbors from scratch to classify a Develop Health patient record using Euclidean distance and majority voting.

MathArraysSearchingphData
Common Model Evaluation MetricsEasy

Explain common machine learning evaluation metrics and when each is useful.

PrecisionAccuracyRecallphData
Optimize ML Pipeline EfficiencyHard

Tests your ability to improve performance, cost, and throughput across an ML pipeline.

ETLBatch ProcessingOrchestrationphData
Diagnose Consistently Inaccurate PredictionsHard

Approach for diagnosing why a model's predictions are consistently inaccurate.

CalibrationAccuracyThreshold TuningphData

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