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Prep plan
Updated weekly · Last refresh Aug 30

Pearson AI Engineer Interview Questions

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

50questions
~8htotal time
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1
CodingStart here. 11 questions · ~110 min
Find Top-K Frequent InteractionsMedium
Practice

Count Pearson MyLab interactions and return the k most frequent using a hash map and heap.

Pearson
Compute Document Embedding SimilarityEasy
Practice

Compute cosine similarity between two Pearson+ document embeddings in one pass with linear time and constant extra space.

function implementationPearson
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2
Generative AI & LLMs11 questions · ~110 min
Reduce Hallucinations in LLM AnswersEasy

Explain LLM hallucination and give three practical ways to reduce it using grounding, prompting, and evaluation.

HallucinationPrompt EngineeringRAGPearson
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3
Model Evaluation6 questions · ~60 min
Manage Production Model DriftHard

Approach for detecting, interpreting, and responding to model drift in a production AI system.

CalibrationAUC-ROCThreshold TuningPearson
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4
System Design11 questions · ~110 min
Design an LLM Serving PlatformHard

Design an LLM serving system that balances latency, cost, scalability, and safety for production traffic.

Cold StartFeature StoreModel ServingPearson
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5
Machine Learning3 questions · ~30 min
Fine-Tuning vs Prompted APIsMedium

Compare when to fine-tune a foundation model versus relying on prompt engineering with a managed API.

Trade-offsPrompt Engineeringmodel fine-tuningPearson
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6
NLP4 questions · ~40 min
Use Embeddings to Improve RelevanceMedium

Assesses understanding of embedding-based retrieval and relevance improvements in education.

search relevancePearson
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7
More topics4 questions · ~40 min
Refactor Monolithic Data PipelinesMedium

Tests your software engineering skills for improving maintainability and testability of data pipelines.

refactoringdata processingPearson
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