Curated · Career Switcher
Top 15 Career Switcher Interview Questions
Here are the top 15 AI interview questions for Career Switcher candidates, sorted by community quality. Each entry links to a detailed answer with explanations, hints, and source-grade follow-ups. Browse all Career Switcher questions →
Sorted by community quality · refreshed as new questions are published.
- 01Explain scaled dot-product attention.Short AnswerMedium·Qual 4.8
- 02What is the KV cache in transformer inference?FlashcardEasy·Qual 4.7
- 03What is RLHF, and why is it used after pretraining?Multiple ChoiceMedium·Qual 4.7
- 04What does LoRA do, and why is it popular for fine-tuning?Multiple ChoiceMedium·Qual 4.7
- 05Which metric best measures whether a RAG answer is grounded in the retrieved context?Multiple ChoiceMedium·Qual 4.7
- 06When should you fine-tune instead of using RAG?Short AnswerMedium·Qual 4.6
- 07Explain why transformers replaced RNNs for language modeling.Short AnswerMedium·Qual 4.6
- 08What does RAG primarily help with in LLM-based applications?Multiple ChoiceEasy·Qual 4.6OpenAI
- 09Why combine BM25 with dense embeddings for retrieval?Multiple ChoiceEasy·Qual 4.6
- 10PPO vs DPO, what's the practical difference?FlashcardMedium·Qual 4.6
- 11What is the Model Context Protocol (MCP) and what problem does it solve?Multiple ChoiceEasy·Qual 4.6
- 12What distinguishes an AI agent from a plain LLM call?Multiple ChoiceMedium·Qual 4.5
- 13Which components make up a standard transformer block?Multiple ChoiceEasy·Qual 4.5
- 14HNSW vs IVF, when do you pick each for a production vector index?FlashcardMedium·Qual 4.5
- 15How does MCP differ from OpenAI-style function calling?FlashcardMedium·Qual 4.5
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