Top 15
Prep plan
Updated weekly · Last refresh Aug 30

Handshake Machine Learning Engineer Interview Questions

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

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~2htotal time
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1
Machine LearningStart here. 4 questions · ~33 min
Imbalanced Ranking and RecommendationsMedium

Tests your approach to training and evaluating models under class imbalance for ranking and recommendations.

data preprocessingmodel trainingRecommendation SystemsHandshake
Feature Selection and EngineeringMedium

Tests your ability to reduce dimensionality, prevent leakage, and build strong features for ML models.

data preprocessingFeature EngineeringHandshake
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2
System Design8 questions · ~66 min
Design a Real-Time ML Feature StoreHard

Design a shared feature store for training and low-latency inference across many ML systems with strict freshness and consistency needs.

Feature StoreFeature DriftModel ServingHandshake
Design Cold Start RecommendationsHard

Design a recommendation system strategy for new users and new items when interaction history is sparse or missing.

Cold StartFeature StoreRecommendation SystemsHandshake
Design Personalized Job RecommendationsMedium

Design an end-to-end ML system for personalized job recommendations at marketplace scale, including retrieval, ranking, serving, and monitoring.

Feature StoreFeature DriftModel ServingHandshake
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3
More topics3 questions · ~25 min
Online vs Offline EvaluationMedium

Tests your understanding of offline metrics, online experimentation, and causal impact measurement.

model performanceHandshake
Clean and Process Streaming DataMedium

Tests your ability to build robust data pipelines for streaming ingestion and preprocessing.

data cleaningfunction implementationHandshake
Structure Data for Efficient RetrievalMedium

Tests your data modeling skills for fast lookup and retrieval in recommendation or ranking systems.

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