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Electronic Arts (Ea) Machine Learning Engineer Interview Questions

The questions to prepare for a Electronic Arts (Ea) Machine Learning Engineer interview. Questions from real interview reports rank first. Updated weekly.

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1
Machine LearningStart here. 6 questions · ~48 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 TradeoffElectronic Arts (Ea)
Model Optimization Techniques in PracticeMedium

Explain practical model optimization techniques, including regularization, cross-validation, and hyperparameter tuning, grounded in a real ML workflow.

Feature EngineeringDeep LearningSupervised LearningElectronic Arts (Ea)
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2
Behavioral & Leadership7 questions · ~56 min
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3
More topics8 questions · ~64 min
Cleaning Missing Values in PipelinesEasy

Approach for handling missing values in a pipeline with data quality checks and repeatable transformations.

Data WranglingETLQualityElectronic Arts (Ea)
Explain Core Classification MetricsEasy

Explain precision, recall, F1-score, and ROC-AUC for a classification model.

F1 ScorePrecisionAUC-ROCElectronic Arts (Ea)
Gaming Recommendation System DesignHard

Tests system design skills for building scalable, effective recommendations in a game publishing context.

ML RankingRetrievalRecommendation SystemsElectronic Arts (Ea)
Attention and TransformersHard

Evaluates your understanding of core transformer components and how attention enables sequence modeling.

transformersDeep LearningElectronic Arts (Ea)
Validate a Machine Learning ModelEasy

How to validate a machine learning model and interpret whether its metrics are trustworthy.

PrecisionAccuracyRecallElectronic Arts (Ea)
Improving Game AI FactorsMedium

Tests your approach to diagnosing and improving AI behavior using data, metrics, and constraints.

Feature StoreModel ServingRecommendation SystemsElectronic Arts (Ea)
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