Top 49
Prep plan
Updated weekly · Last refresh Aug 30

Reply AI Engineer Interview Questions

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

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1
CodingStart here. 7 questions · ~66 min
Design an LRU CacheEasy
Practice
Recently asked

Implement an LRU cache in O(1) average time using a hash table and doubly linked list.

Hash TablesQueueLinked ListsReply
Binary Tree Level Order TraversalEasy
Practice
Recently asked

Traverse a binary tree level by level using a queue-based breadth-first search.

QueueTreesReply
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2
System Design8 questions · ~75 min
Design Cold Start for RecommendationsHard

Design a recommendation system strategy for model cold start and new-user cold start, including serving, evaluation, and safe rollout.

Cold StartRetrievalTwo-Tower ModelsReply
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3
Generative AI & LLMs6 questions · ~56 min
Evaluate an LLM SystemMedium
Recently asked

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

HallucinationPrompt EngineeringLLM EvaluationReply
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4
Model Evaluation3 questions · ~28 min
Choose Metrics for Imbalanced DataMedium
Recently asked

Choose the right evaluation metric for an imbalanced dataset and explain why accuracy can mislead.

F1 ScorePrecisionAUC-ROCReply
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5
Pipelines6 questions · ~56 min
Backfilling Missing Pipeline DataMedium
Recently asked

Approach for safely backfilling missing data while preserving correctness, idempotency, and data quality.

ETLQualityReply
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6
Machine Learning3 questions · ~28 min
Handling Class Imbalance in ClassificationMedium
Recently asked

Explain practical ways to train and evaluate a classifier when the target classes are highly imbalanced.

model trainingSupervised LearningClass ImbalanceReply
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7
More topics16 questions · ~150 min
Explain Transformer Self-AttentionHard
Recently asked

Explain how transformer self-attention works, including its role in sequence modeling and why it scales better than RNNs.

Neural NetworksLanguage ModelsDeep LearningReply
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