Top 50 AI, ML & Generative AI Interview Questions in 2027

Getting an AI job isn’t hard if you learn smartly, focus on the right skills and practice consistently. Here are the 50 questions interviewers ask most in AI, ML and Generative AI in 2027. Go through the list and check how many you can already answer. All 50 answers are in one free cheat sheet at the end of this article.

Part 1: LLM foundations

  1. Transformer
  2. Self-attention
  3. Tokenization
  4. Embeddings
  5. Context window
  6. Next-token prediction
  7. Temperature & top-p
  8. KV cache
  9. Hallucination
  10. Encoder vs decoder

Part 2: Prompting and building LLM apps

  1. Zero-shot vs few-shot
  2. Chain-of-thought
  3. System prompt
  4. Structured output
  5. Function / tool calling
  6. Context engineering
  7. Prompt caching
  8. Streaming
  9. Model routing
  10. Reasoning models

Part 3: RAG and retrieval

  1. RAG
  2. Chunking strategy
  3. Vector database
  4. Cosine similarity
  5. ANN search (HNSW)
  6. Hybrid search
  7. Reranking
  8. Query rewriting
  9. Grounding & citations
  10. Agentic RAG

Part 4: Agents and safety

  1. AI agent
  2. ReAct pattern
  3. Agent memory
  4. Task planning
  5. Multi-agent systems
  6. MCP
  7. Human-in-the-loop
  8. Guardrails
  9. Prompt injection
  10. Workflows vs agents

Part 5: Fine-tuning, evaluation and production

  1. Fine-tuning vs RAG vs prompting
  2. LoRA
  3. QLoRA
  4. RLHF & DPO
  5. Eval sets
  6. LLM-as-judge
  7. RAG metrics
  8. Observability & tracing
  9. Quantization
  10. TTFT & throughput

Get all 50 answers in one cheat sheet

Each question is answered in four parts: what it is, how it works, an example, and an interview tip. The cheat sheet also has diagrams for LLMs, RAG and agents, plus a one-line revision table.

Learn it hands-on

Want to build with these concepts, not just answer questions? Our live Bangla courses cover all 50:

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