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Updated weekly · Last refresh Aug 30

bet365 AI Engineer Interview Questions

The questions to prepare for a bet365 AI Engineer interview. Questions from real interview reports rank first. Updated weekly.

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1
CodingStart here. 5 questions · ~49 min
Binary Tree Level Order TraversalEasy
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Traverse a binary tree level by level using a queue-based breadth-first search.

QueueTreesbet365
Merge Overlapping IntervalsEasy
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Merge overlapping intervals in a list of intervals.

ArraysSearchingSortingbet365
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2
Machine Learning5 questions · ~49 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 Tradeoffbet365
Handling Overfitting in Predictive ModelsMedium

Explain how to diagnose and reduce overfitting using regularization, validation strategy, and model complexity controls.

Cross-ValidationBias-Variance TradeoffRegularizationbet365
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3
System Design6 questions · ~58 min
Design Feature Drift Monitoring SystemHard

Design a production ranking system with robust feature drift monitoring across batch and real-time features at high QPS.

Feature StoreFeature DriftModel Servingbet365
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4
Generative AI & LLMs5 questions · ~49 min
Explain Vector Search in RAGMedium

Design a grounded document Q&A system and explain how vector search improves retrieval quality, latency, and hallucination control in RAG.

Vector SearchPrompt EngineeringRAGbet365
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5
Pipelines3 questions · ~29 min
Cleaning Missing Values in PipelinesEasy

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

Data WranglingETLQualitybet365
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6
Model Evaluation4 questions · ~39 min
Choose Classification MetricsMedium

Choose the right classification metrics, and explain when precision, recall, and F1 score matter most.

F1 ScorePrecisionRecallbet365
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7
More topics13 questions · ~126 min
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The finish line: interview-readyComplete all 41 questions to finish this plan.