Top 21
Prep plan
Updated weekly · Last refresh Aug 30

Meta AI Research Scientist Interview Questions

The questions to prepare for a Meta AI Research Scientist interview. Questions from real interview reports rank first. Updated weekly.

21questions
~3htotal time
Track your progressSign up free to work through all 21 questions and resume where you left off.
Start practicing free →
1
Generative AI & LLMsStart here. 4 questions · ~34 min
Reduce Hallucinations in LLM AnswersEasy

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

HallucinationPrompt EngineeringRAGMeta
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 EngineeringRAGMeta
More Generative AI & LLMs questions with a free account
2
System Design3 questions · ~25 min
Design Feature Drift Monitoring SystemHard
Recently asked

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

Feature StoreFeature DriftModel ServingMeta
Design Two-Tower Candidate RetrievalHard

Design a two-tower candidate retrieval system for a large personalized feed with 600M items and tight latency budgets.

Feature StoreRetrievalTwo-Tower ModelsMeta
More System Design questions with a free account

Sign up to see every question

Create a free account to unlock this list and practice real interview questions.

Get my prep plan
3
Behavioral & Leadership9 questions · ~75 min
More Behavioral & Leadership questions with a free account
4
More topics5 questions · ~42 min
Power Analysis for Experiment PlanningMedium

Reason about power analysis when planning an experiment and choosing sample size.

ExperimentationPower AnalysisSample SizeMeta
Choosing a Classifier ThresholdMedium

Explain how to choose a classifier threshold using precision, recall, calibration, and business tradeoffs.

Confusion MatrixPrecisionThreshold TuningMeta
Use Word Embeddings in Text AnalyticsHard

Explain how to apply word embeddings in a text analytics workflow, from preprocessing to modeling and evaluation.

Language ModelsText ClassificationWord EmbeddingsMeta
Statistical Significance in Hypothesis TestingEasy

Explain what statistical significance means and why it matters when interpreting experimental or analytical results.

Hypothesis TestingData AnalysisStatistical SignificanceMeta
More questions with a free account
The finish line: interview-readyComplete all 21 questions to finish this plan.