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Updated weekly · Last refresh Sep 26

Seatgeek Machine Learning Engineer Interview Questions

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

16questions
~2htotal time
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1
Machine LearningStart here. 7 questions · ~56 min
Handling Imbalanced Fraud LabelsMedium

Explain how to train and evaluate models on highly imbalanced fraud data without relying on misleading accuracy.

Cross-ValidationFeature EngineeringSupervised LearningSeatgeek
Model Drift and RetrainingMedium

Assesses monitoring and detection of data/model drift and retraining triggers.

Model EvaluationSeatgeek
High-Cardinality Feature EngineeringMedium

Tests approach to encoding high-cardinality features effectively.

data preprocessingFeature EngineeringSeatgeek
Cold-Start in SeatGeek RecommendationsMedium

Tests ability to address cold-start in a SeatGeek-like recommendation system.

Recommendation SystemsSeatgeek
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2
System Design5 questions · ~40 min
Inference Latency OptimizationHard

Evaluates techniques to reduce inference latency in production at SeatGeek.

Seatgeek
Production Model MonitoringMedium

Evaluates monitoring, alerts, and reliability for deployed models.

performance evaluationSeatgeek
Real-Time Recommendation SystemHard

Tests system design for high-throughput real-time recommendations in SeatGeek's domain.

scalabilityreal-time systemsSeatgeek
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3
Behavioral & Leadership4 questions · ~32 min
Resolving Technical Trade-off ConflictMedium

Tests conflict resolution on technical trade-offs, including influence without authority, stakeholder management, and outcome ownership.

Decision MakingConflict ResolutionStakeholder ManagementSeatgeek
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