About the job
Airbnb was established in 2007 when two hosts welcomed three guests into their San Francisco home. Since then, it has expanded to over 5 million hosts who have received more than 2 billion guests across nearly every country worldwide. Each day, hosts provide unique accommodations and experiences, allowing guests to connect with communities in a meaningful and authentic manner.
The Community You Will Join:
Community Support (CS) plays a pivotal role in driving Airbnb's core business. Our Community Support Engineering team is tasked with developing state-of-the-art technology, architecture, and solutions that empower CS at Airbnb. The innovations we create enhance the experiences of guests, hosts, CS agents, and operations teams globally.
Aligned with our CS Product vision, we are harnessing the power of AI to revolutionize our customer service delivery, merging sophisticated ML/LLM capabilities with the expertise of our Support Ambassadors to provide a seamless, high-quality support experience.
The Impact You Will Have:
As the ML Manager for Community Support Product Engineering in China, you will lead a talented team of machine learning engineers. Your focus will be on researching, designing, and optimizing AI models and services that scale our AI-driven products and significantly enhance the Community Support experience for guests, hosts, and support ambassadors.
Your Responsibilities Will Include:
- Recruit, mentor, and develop a dynamic team of skilled machine learning engineers, promoting their technical and professional growth.
- Take proactive initiatives to achieve results that extend beyond the team's scope.
- Build strong relationships and ensure alignment with stakeholders within Community Support and across external teams.
- Effectively communicate complex concepts and decisions to various stakeholders across different functions.
- Provide essential guidance and input for prioritizing multiple significant projects.
Collaborate closely with platform, backend, and frontend engineers to facilitate rapid development cycles without compromising quality, developing robust ML models and systems that enhance community support initiatives. Conduct comprehensive design and architecture reviews to continually elevate our standards of technical excellence.

