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Prep plan
Updated weekly · Last refresh Aug 30

Rakuten NLP Engineer Interview Questions

The questions to prepare for a Rakuten NLP Engineer interview. Questions from real interview reports rank first. Updated weekly.

25questions
~3htotal time
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1
System DesignStart here. 4 questions · ~33 min
Deploy a Cloud ML ModelMedium

Design a production ML deployment on Google Cloud with serving, feature management, rollout, monitoring, and evaluation.

InfrastructureFeature StoreModel ServingRakuten
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 SystemsRakuten
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2
NLP5 questions · ~42 min
Classify Customer Feedback SentimentMedium

Build a sentiment classifier for customer feedback using modern text preprocessing and transformer fine-tuning.

Text ClassificationSentiment AnalysisTokenizationRakuten
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3
Model Evaluation3 questions · ~25 min
Improving an Existing NLP ModelMedium

Tests iterative improvement approach using diagnostics, evaluation, and targeted changes.

Cross-ValidationF1 ScoreThreshold TuningRakuten
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4
Coding5 questions · ~42 min
Using NLTK or spaCy in CodeEasy

Tests proficiency with NLP tooling and applying it correctly in code.

Hash TablesArraysStringsRakuten
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5
Behavioral & Leadership5 questions · ~42 min
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6
More topics3 questions · ~25 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 TradeoffRakuten
Integrating External APIs for NLPMedium

Tests design of tool use, latency management, and robustness when NLP depends on external services.

Structured ExtractionRAGLLM AgentsRakuten
Structuring Text Data PreprocessingMedium

Tests ability to build reproducible preprocessing steps for NLP training and inference.

ETLBatch ProcessingQualityRakuten

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