Staff Machine Learning Engineer, Listings and Host Tools Data and AI

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), 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 these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), data warehouse (eg. Hive) - Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models, as well as integrating to product use cases. - Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models) - Experience with test driven development, familiar with A/B testing, incremental delivery and deployment. Your Location: This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Our Commitment To Inclusion & Belonging: Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected]. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This ro

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 (e.g., training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g., gradient boosted trees, neural networks/deep learning, optimization, state-of-the-art NLP and CV algorithms) and domains (e.g., natural language processing, computer vision, personalization and recommendation, anomaly detection). Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), data warehouse (e.g., Hive). Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models, as well as integrating to product use cases. Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models). Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.

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.