Generative AI & LLM Interview Questions and Answers

Are You Ready to Crack the Toughest AI Interviews?

The landscape of tech interviews has changed. Standard Machine Learning questions aren’t enough anymore. Recruiters and Hiring Managers are now drilling deep into Generative AI and Large Language Models (LLMs).

Are you prepared to explain how Attention Mechanisms work on a whiteboard? Can you confidently discuss the trade-offs between Fine-tuning and RAG?

“Generative AI & LLM Interview Questions and Answers” is the definitive preparation guide designed to bridge the gap between theory and the interview room. We have compiled real-world questions asked by FAANG (MAANG) companies and top AI startups to ensure you walk into your interview with total confidence.

What’s Inside?

We go beyond surface-level definitions. This guide covers the full spectrum of the modern AI stack:

• Core Architectures: Deep dives into Transformers, Encoders/Decoders, BERT vs. GPT, and Attention Mechanisms (Self-Attention, Multi-Head).

• LLM Lifecycle: Pre-training, Fine-tuning (LoRA, QLoRA), and RLHF (Reinforcement Learning from Human Feedback).

• Advanced Techniques: Retrieval-Augmented Generation (RAG), Vector Databases, Prompt Engineering, and Context Windows.

• GenAI Challenges: Handling Hallucinations, Bias, Ethics, and Model Evaluation metrics (Perplexity, BLEU, ROUGE).

• Coding & System Design: Practical scenarios, such as “How would you design a chatbot for a specific domain?” or “Write the loss function for a standard LLM.”

Who Is This For?

“A must-have resource for anyone transitioning into the GenAI space.”

• Aspiring AI Engineers: Build a solid foundation to pass entry-level and mid-level screenings.

• Senior Data Scientists: Refresh your knowledge on the latest bleeding-edge architectures.

• Technical Product Managers: Understand the “how” and “why” behind the models you manage.