Airbnb
Senior
Build the agentic AI stack behind Airbnb's Chat, Voice, and Human-Agent Assist products
Airbnb's Community Support ML team owns the Chat AI assistant, Voice AI Assistant, and Human Agent Assistant that serve guests and hosts worldwide. This interview probes hands-on LLM expertise — fine-tuning, RAG, and multi-agent orchestration — plus the ability to ship production-grade ML systems and work cross-functionally with product and design from ambiguous, early-stage ideas to shipped features.
走进这场面试
免费 · 一场按这个岗位校准的真语音模拟
这场面试考什么
- LLM fine-tuning (SFT, RLHF, GRPO) and prompt engineering
- Agentic system design (multi-agent orchestration, tool-use, memory, ReAct/LangGraph-style pipelines)
- RAG architecture for grounding responses in account/policy context
- Production ML infrastructure, model serving, and MLOps at scale
- LLM evaluation frameworks and guardrails for a customer-facing assistant
- Cross-functional communication with product, design, and engineering on 0-to-1 initiatives
常见提问方向
Design a chat or voice AI agent that can safely escalate to a human when uncertain
Describe a time you fine-tuned or distilled an LLM and how you measured the improvement
How would you build an evaluation framework for a customer-support AI assistant
Tradeoffs between building a custom agentic pipeline vs. using an existing framework
How do you guard against hallucinated policy answers in a support context
相关面试
Airbnb
Mid
Software Engineer, Quality Platform
Airbnb
Senior
Senior Software Engineer, Reliability Engineering Team
Airbnb
Staff
Staff Machine Learning Engineer, Customer Support Engineering
Senior
Sr. Machine Learning Engineer, Responsible AI (Applied Research Science)
Roblox
Senior
Senior Machine Learning Engineer, Ads
Roblox
Senior