Top 50 LLM Evaluation Interview Questions
The most frequently asked LLM Evaluation questions across all roles and companies, ranked by real interview frequency. Updated daily.
Explain how to evaluate a generative model using offline and online methods, with attention to hallucination, product metrics, and experiment design.
CACI
Capgemini
American AirlinesExplain a practical approach to fine-tuning an LLM for a specific task, including data, evaluation, and hallucination risks.
Ernst & Young
XometryPPSEGDiscuss the main ethical risks in deploying generative AI, including hallucination, misuse, privacy, and governance.
Dell
Agentic
Amazon ServicesDiscuss how you designed an LLM system for a business use case, including evaluation, hallucination control, and cost latency tradeoffs.
Faraday Future
The Boston Consulting Group
Uber DriversDesign an eval framework for LLM quality, safety, usefulness, cost, and latency beyond perplexity.
Fuse Energy
Bank of America
SandiskDesign and evaluate a RAG assistant over internal policy and delivery docs with strict latency, cost, and hallucination limits.
Applied Medical
Foundation Robotics Labs
OtsukaExplain context windows, tokenization, and the main technical issues with long-context LLM inputs, plus practical ways to handle them.
Infosys
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Select and justify the evaluation metrics needed to move an LLM from prototype testing to reliable production monitoring.