Top 11
Prep plan
Updated weekly · Last refresh Aug 30

Sberbank Machine Learning Engineer Interview Questions

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

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1
Machine LearningStart here. 3 questions · ~25 min
Model Selection Tradeoffs at ScaleHard

Reason about model choice for large-scale deployment, balancing accuracy, latency, stability, and maintenance cost.

Hyperparameter TuningCross-ValidationBias-Variance TradeoffSberbank
Model Selection Tradeoffs at ScaleMedium

Assesses your ability to build and apply churn prediction models using historical banking data.

predictive modelingSberbank
Customer Outflow PredictionMedium

Evaluates your approach to building an ML model for customer churn at Sberbank.

predictive modelingDebuggingcollaborationSberbank
2
Behavioral & Leadership4 questions · ~33 min
Improving Version Control CollaborationEasy

Tests ownership and communication through improving Git-based collaboration, code review practices, and merge conflict handling.

CommunicationLeadershipOwnershipSberbank
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3
More topics4 questions · ~33 min
Data Quality in ML PipelinesMedium

Approach for maintaining high quality data across ML pipelines, from ingestion through feature generation and model consumption.

Data QualityInfrastructureData WranglingSberbank
Solving Complex Programming ProblemsMedium

Tests structured problem solving and engineering judgment under complexity.

Programmingtechnical proficiencySberbank
Optimizing ML Pipeline QueriesMedium

Tests performance tuning skills and how you connect data layer changes to ML pipeline outcomes.

database optimizationperformanceSberbank
Solving Complex Programming ProblemsMedium

Evaluates problem-solving, debugging, and optimization skills for complex programming tasks.

Data StructuresDebuggingAlgorithmsSberbank

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