Senior Machine Learning Engineer, Users & Contextualization Team

Airbnb was born in 2007 when two Hosts welcomed three guests to their San Francisco home, and has since grown to over 4 million Hosts who have welcomed more than 1 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:

The Users & Contextualization Team's mission is to build a robust foundation for understanding Airbnb Guest & hosts using both structured and unstructured data and provides data driven solutions to achieve personalized experience on Airbnb. These products will power but are not limited to improving on-boarding experience, Profile optimization , personalized experience of Airbnb products.

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 a senior 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.

Your Expertise:

• 5+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
• Must have experience in both Natural Language Processing and Computer Vision.
• 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), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization, state-of-art NLP and CV algorithms) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection)
• Experience with 3 or more of …