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 and evaluate a RAG assistant over internal policy and delivery docs with strict latency, cost, and hallucination limits.
Applied Medical
Foundation Robotics Labs
OtsukaTalk through a real generative AI project, focusing on architecture, evaluation, hallucination risk, and how you handled safety issues in practice.
Xometry
CGI
Capgemini Government SolutionsDesign a safe LLM workflow that explains prompt injection to technical customers without hallucinating or overstating security guarantees.
OpenAI
Remitly
Zone 5 TechnologiesExplain context windows, tokenization, and the main technical issues with long-context LLM inputs, plus practical ways to handle them.
Infosys
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