Top 35
Prep plan
Updated weekly · Last refresh Sep 25
M

monday AI Engineer Interview Questions

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

35questions
~5htotal time
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1
Machine LearningStart here. 8 questions · ~64 min
Loss Functions for ClassificationMedium

Tests understanding of loss behavior and how it affects performance and calibration in ML models.

Classificationloss functionsModel Evaluationmmonday
Time Series Feature EngineeringMedium

Design lag, rolling, and calendar features for a forecasting problem with temporal dependence.

Feature EngineeringSupervised LearningTime Seriesmmonday
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2
System Design9 questions · ~72 min
Design a Multi Agent Coordination SystemHard

Design the infrastructure for a multi-agent system where agents communicate, coordinate work, and recover from non-deterministic failures.

Feature StoreModel ServingRecommendation Systemsmmonday
Design a Low Latency Inference PlatformHard

Design a low latency ML inference platform for high-frequency online predictions with strict response times and evolving model features.

high-frequency requestslatencysystem architecturemmonday
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3
Model Evaluation3 questions · ~24 min
Monitor Model Performance Over TimeMedium

Approach for continuously monitoring a deployed model and keeping performance stable as data changes.

CalibrationAccuracyThreshold Tuningmmonday
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4
Generative AI & LLMs3 questions · ~24 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 Evaluationmmonday
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5
Pipelines3 questions · ~24 min
Data Quality in ETL PipelinesEasy

Approach for maintaining data quality and integrity across ETL pipelines.

IdempotencyData ModelingQualitymmonday
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6
Behavioral & Leadership8 questions · ~64 min
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7
More topics1 question · ~8 min
Embeddings and Vector SearchMedium

Tests your understanding of representation learning and retrieval for better AI outcomes.

Vector Searchmmonday
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