Senior Machine Learning Engineer, Customer Support Engineering
Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Machine Learning @ 4
MLOps @ 7
Communication @ 4
React @ 4
LLM @ 4
AI @ 4
Reinforcement Learning @ 4
Agentic AI @ 4
RAG @ 4
Prompt Engineering @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. The Core ML team in Community Support is responsible for adopting Agentic AI technologies to enable an intelligent, scalable and exceptional customer service experience. The team develops the Chat AI assistant, Voice AI Assistant and more, exploring SOTA agentic architectures and leveraging tools including SFT, reinforcement learning, distillation, RAG/search, LLM evaluation and testing automation, feedback-based learning and guardrails.
Responsibilities
- Champion the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.
- Work cross-functionally with product, design, and other engineering counterparts to design and build efficient AI solutions for Airbnb customer service products.
- Build and leverage cutting-edge AI technologies to transform Airbnb’s customer service by delivering personalized, easy-to-use and proactive experiences.
- Shape initiatives from inception to production, turning conceptual ideas into production-grade systems.
- Learn and share the latest AI/ML technologies with the team.
Requirements
- PhD or Master's degree with 6+ years of experience in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field — or equivalent industry experience.
- Hands-on expertise in large language models (LLMs), including pretraining and fine-tuning approaches such as SFT, RLHF, and GRPO.
- Experience with 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 (examples cited: ReAct, LangGraph, AutoGen, or similar).
- Experience shipping production-grade ML/AI systems at scale, with deep understanding of ML infrastructure, model serving, and MLOps best practices.
- Excellent communication skills and ability to collaborate across Engineering, Product, and Design.
Location
This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager. Candidates must live in a state where Airbnb, Inc. has a registered entity (see Airbnb careers for excluded states). If employed by another Airbnb entity, recruiters will provide eligibility details.
Commitment to Inclusion & Belonging
Airbnb is committed to working with the broadest talent pool possible and encourages all qualified individuals to apply. The company provides a disability-inclusive application and interview process and offers reasonable accommodations on request ([email protected]).
Compensation
Base pay range: $196,000—$227,000 USD. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. The actual base pay is dependent on factors such as training, transferable skills, work experience, business needs and market demands.