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Updated weekly · Last refresh Aug 30

Santander Consumer Usa AI Engineer Interview Questions

The questions to prepare for a Santander Consumer Usa AI Engineer interview. Questions from real interview reports rank first. Updated weekly.

35questions
~6htotal time
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1
CodingStart here. 5 questions · ~48 min
Reverse a Linked ListEasy
Practice

Reverse a singly linked list in place using pointer manipulation.

RecursionLinked ListsSantander Consumer Usa
Find Two Sum IndicesEasy
Practice

Use a hash map to find two array elements that sum to a target in O(n) time.

Hash TablesArraysSortingSantander Consumer Usa
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2
System Design4 questions · ~38 min
Design a Secure Scalable ML PlatformMedium

Design a production ML decision service with low latency serving, secure data handling, and scalable training and inference.

Feature StoreRetrievalModel ServingSantander Consumer Usa
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3
Machine Learning3 questions · ~29 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 LearningSantander Consumer Usa
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4
Model Evaluation3 questions · ~29 min
Detect Production Drift in ModelsHard

How to detect data drift and concept drift in production using metric shifts, control charts, and calibration checks.

CalibrationAUC-ROCThreshold TuningSantander Consumer Usa
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5
Pipelines3 questions · ~29 min
Data Quality and Schema EvolutionMedium

Approach for handling schema changes and data quality checks in a high-volume data lake pipeline.

schema evolutionData ModelingQualitySantander Consumer Usa
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6
Generative AI & LLMs4 questions · ~38 min
Evaluate an LLM SystemMedium

Explain how to evaluate a generative model using offline and online methods, with attention to hallucination, product metrics, and experiment design.

HallucinationPrompt EngineeringLLM EvaluationSantander Consumer Usa
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7
More topics13 questions · ~124 min
Tokenize Text for NLP PipelinesEasy

Explain tokenization and how it prepares text for downstream NLP models and features.

Language ModelsText ClassificationTokenizationSantander Consumer Usa
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