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Updated weekly · Last refresh Sep 20

University of Chicago AI Engineer Interview Questions

The questions to prepare for a University of Chicago AI Engineer interview. Questions from real interview reports rank first. Updated daily.

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1
Machine LearningStart here. 9 questions · ~72 min
Describe an ML Project and ChallengesEasy

Discuss a machine learning project you have worked on and the challenges you faced.

Hyperparameter TuningCross-ValidationFeature EngineeringUniversity of Chicago
Feature Selection for ML ModelsMedium

Choose useful features for a supervised model and avoid overfitting, leakage, and unstable predictors.

Cross-ValidationFeature EngineeringBias-Variance TradeoffUniversity of Chicago
Handle Imbalanced Classification DataMedium

Build a classifier for a highly imbalanced dataset and choose metrics, sampling, and thresholds that fit the minority class.

Cross-ValidationFeature EngineeringSupervised LearningUniversity of Chicago
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2
Pipelines3 questions · ~24 min
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualityUniversity of Chicago
Reproducible GeoJSON PipelineHard

Tests your ability to build reliable, repeatable data pipelines with production-grade engineering.

ETLIdempotencyQualityUniversity of Chicago
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3
More topics4 questions · ~32 min
Evaluate Precision and Recall TradeoffsMedium

Assess precision and recall for a model and explain how the threshold changes the tradeoff.

F1 ScorePrecisionRecallUniversity of Chicago
Build Reproducible CodeMedium

Assesses your approach to reproducibility in AI engineering workflows and code execution.

best practicesUniversity of Chicago
GeoJSON Distance Output PipelineMedium

Tests your ability to build a correct geospatial transformation pipeline and produce valid outputs.

MathArraysData WranglingUniversity of Chicago
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