Machine Learning Engineer, Community Support Engineering

Airbnb Airbnb · Consumer · United States · Software Engineering

Machine Learning Engineer focused on adopting Agentic AI technologies for customer service at Airbnb. This role involves developing AI assistants (Chat, Voice), exploring SOTA Agentic architectures, and enhancing AI models and ML services. Responsibilities include building and leveraging cutting-edge AI for personalized customer service, shaping ideas from inception to production, and working cross-functionally. Requires expertise in LLMs (pretraining, fine-tuning, RAG, evaluation) and building Agentic AI systems (orchestration, tool-use, reasoning). Experience shipping production-grade ML/AI systems at scale is essential.

What you'd actually do

  1. Champion the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems
  2. Work cross-functionally with product, design, and other engineering counterparts to design and build efficient AI solutions for Airbnb CS products
  3. Learn and share the latest AI/ML technologies with the team.

Skills

Required

  • PhD w/ 3+ YOE in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field — or equivalent industry experience
  • Hands-on expertise in LLM, including pretraining, fine-tuning (SFT, RLHF, GRPO), prompt engineering, RAG architectures, and LLM evaluation frameworks
  • Experience building Agentic AI systems — including multi-agent orchestration, tool-use, planning, memory, and autonomous reasoning pipelines (e.g., ReAct, LangGraph, AutoGen, or similar)
  • Experience of shipping production-grade ML/AI systems at scale, with deep understanding of ML infrastructure, model serving, and MLOps best practices
  • Excellent communication skills with the ability to collaborate effectively across Engineering, Product, and Design organizations

What the JD emphasized

  • Agentic AI technologies
  • Chat AI assistant
  • Voice AI Assistant
  • Agentic AI systems
  • shipping production-grade ML/AI systems at scale

Other signals

  • developing the Chat AI assistant, Voice AI Assistant
  • adopting the Agentic AI technologies
  • shipping production-grade ML/AI systems at scale