Top 13
Prep plan
Updated weekly · Last refresh Aug 30

Notion Labs AI Engineer Interview Questions

The questions to prepare for a Notion Labs AI Engineer interview. Questions from real interview reports rank first. Updated weekly.

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1
CodingStart here. 3 questions · ~28 min
Linear Regression From ScratchMedium
Practice

Fit a univariate linear regression model from data using gradient descent or the normal equation.

MathArraysGradient DescentNotion Labs
Complexity AnalysisEasy

Tests your ability to analyze algorithmic efficiency and resource usage.

ArraysSearchingSortingNotion Labs
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2
Machine Learning4 questions · ~37 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 TradeoffNotion Labs
Feature Engineering for ML ModelsEasy

Explain how feature engineering improves supervised models and how to choose useful transformations.

Cross-ValidationFeature EngineeringModel EvaluationNotion Labs
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3
Model Evaluation3 questions · ~28 min
Model Performance EvaluationEasy

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

PrecisionAccuracyRecallNotion Labs
Diagnose Consistently Inaccurate PredictionsHard

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

CalibrationAccuracyThreshold TuningNotion Labs
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4
Pipelines3 questions · ~28 min
Prepare Training Data PipelineMedium

Outline a repeatable pipeline for cleaning, validating, and preparing a dataset for model training.

ETLData ModelingQualityNotion Labs
Production ML Deployment PipelineMedium

Key production pipeline considerations for deploying, validating, and monitoring an ML model.

InfrastructureIdempotencyQualityNotion Labs
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The finish line: interview-readyComplete all 13 questions to finish this plan.