Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way
The Community You Will Join: Listings and Host Tools Data and AI (DnA) team: This team supports host personalization products and provides data driven solutions to achieve superior host experience on Airbnb. These products include but are not limited to managing your space (MYS), host tools etc. We own data pipelines and ML models and will build services for serving that are used in the above areas
The Difference You Will Make: There is a huge opportunity to improve the Host and Guest experience by leveraging open source, third party, and home grown ML models. As an ML engineer, you will partner closely with our data science, product partners, and other ML + data engineers on the team to execute on these opportunities in order to improve the Host and Guest product experience on Airbnb
A Typical Day: Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases
Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact
Prototype machine learning use cases for use in the product, and work with stakeholders to iterate on requirements
Develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases
Design and build services, API to enable serving ML model driven data to product use cases
Your Expertise: 8+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields
Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algori