Software Engineer, Machine Learning
🇺🇸 United States › California › San Francisco (Posted Sep 16 2018)
About the company
Founded in August of 2008 and based in San Francisco, California, Airbnb is a trusted community marketplace for people to list, discover, and book unique accommodations around the world — online or from a mobile phone. Whether an apartment for a night, a castle for a week, or a villa for a month, Airbnb connects people to unique travel experiences, at any price point, in more than 33,000 cities and 192 countries. And with world-class customer service and a growing community of users, Airbnb is the easiest way for people to monetize their extra space and showcase it to an audience of millions.
We are looking for Machine Learning engineers to join our growing team. In this role, you’ll have the opportunity to work on challenging data problems, including:
Large scale Machine Learning infrastructure that powers our Search ranking models.
Natural Language Processing to understand text content on Airbnb platform, including reviews, descriptions and interactions between users on our marketplace.
Identifying suspicious transactions and malicious users for Trust and Safety.
Determining the optimal pricing strategies to help our Hosts effectively manage their listings and achieve their revenue goals.
Modeling demand and supply situation in real time to optimize the overall market efficiency and give valuable insights to the Hosts.
Clustering of users and listings to enable more intelligent matching.
Skills & requirements
5+ years of industry experience or a PhD + 2 years industry experience
Solid engineering and coding skills. Ability to write high performance production quality code. Experience in Java, C++, Python, Scala and other equivalent languages is a plus.
Industry experience building and productionizing innovative end-to-end Machine Learning systems.
Good understanding of common families of models, feature engineering, feature selection and other practical machine learning issues, such as overfitting.
Experience with MapReduce, Spark and Hive a plus.
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