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Prep plan
Updated weekly · Last refresh Aug 30

Waymo Machine Learning Engineer Interview Questions

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

37questions
~5htotal time
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1
PipelinesStart here. 4 questions · ~33 min
Handling Missing Data in PipelinesMedium

Approach for handling missing data in an ML data pipeline, including validation, imputation, and safe downstream consumption.

InfrastructureETLBatch ProcessingWaymo
End-to-End Sensor Data PipelineHard

Tests ability to architect data pipelines from ingestion and labeling to training, validation, and deployment.

ETLBatch ProcessingData ModelingWaymo
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2
Machine Learning16 questions · ~132 min
Transfer Learning for Vision ModelsMedium

Explain transfer learning and why starting from a pretrained model can improve supervised learning on limited labeled data.

Neural NetworksFeature EngineeringDeep LearningWaymo
Decision Tree Pros and ConsMedium

Explain when decision trees work well, where they fail, and how to evaluate them against simpler or more stable alternatives.

Feature EngineeringDeep LearningSupervised LearningWaymo
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3
Coding6 questions · ~50 min
Numpy and Tensor DebuggingMedium

Assesses your ability to reason about correctness and performance in numerical code.

numpyDebuggingWaymo
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4
System Design4 questions · ~33 min
Latency and Out-of-Memory OptimizationHard

Tests your ability to improve performance while preventing memory failures in production systems.

latencyoptimizationWaymo
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5
Behavioral & Leadership5 questions · ~41 min
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6
More topics2 questions · ~17 min
Safety-Critical Model MetricsMedium

Tests knowledge of evaluation metrics aligned to safety, reliability, and operational risk.

PrecisionAccuracyRecallWaymo
Model Evaluation with Contrastive LearningMedium

Evaluates your ability to choose evaluation methods for contrastive representation models.

Model EvaluationWaymo
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