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Decagon Interview Questions

The questions to prepare for Decagon interviews, across all roles. Questions from real interview reports rank first. Updated weekly.

50questions
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1
CodingStart here. 9 questions · ~85 min
2
Machine Learning10 questions · ~95 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 TradeoffDecagon
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3
Execution8 questions · ~76 min
Handle Scope Changes Mid-DevelopmentMedium

Explain how you manage scope changes during development without losing delivery control, stakeholder alignment, or product quality.

AgileScope ManagementProject ManagementDecagon
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4
Pipelines5 questions · ~47 min
Scaling Data Pipelines EffectivelyMedium

Approach for building data pipelines that scale in throughput, reliability, and operational visibility.

InfrastructureETLDecagon
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5
System Design9 questions · ~85 min
Design a Behavior-Based RecommenderHard

Design a recommendation system that uses user behavior to retrieve, rank, and re-rank items at scale.

ML RankingFeature StoreRecommendation SystemsDecagon
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6
Model Evaluation4 questions · ~38 min
Model Performance EvaluationEasy

Tests your ability to select metrics, validation strategy, and interpret results for ML models.

PrecisionAccuracyRecallDecagon
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7
More topics5 questions · ~47 min
Approach LLM Fine-Tuning for TasksMedium

Explain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.

Prompt EngineeringLLM EvaluationFine-TuningDecagon
Chunking and Metadata OptimizationMedium

Tests your ability to improve retrieval quality through document preprocessing choices.

Text ClassificationNLPTokenizationDecagon
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Hands-on SQL practiceWrite and run real queries in the editor. 3 drills · ~30 min
The finish line: interview-readyComplete all 50 questions plus 3 hands-on drills to finish this plan.