The Community You Will Join:

Payments is key for any healthy marketplace, and is just as central to our product at Airbnb. The Payments org at Airbnb is responsible for everything related to settling money in Airbnb’s global marketplace and makes the Payment experience as delightful, magical, intuitive, and easy as possible. At the Payments modeling team, our goal is to empower the mission by introducing intelligences and personalizations that optimize Airbnb’s massive daily transaction volume to best collect payments from guests, distribute payouts to hosts while preventing fraudulent transactions from happening.

The Difference You Will Make:

As a Staff Machine Learning Engineer, your expertise will be pivotal in developing cutting-edge Machine learning solutions including generative AI to define and shape the future of the Airbnb Payments experience. you will also partner with product managers, software engineers, and operation teams to leverage engineering innovations to simplify the business requirements into scalable solutions. 

A Typical Day: 

• Envision, champion, and support the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.
• 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.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• Lead, mentor, challenge and grow enthusiastic, collaborative AI/ML culture within the organization

Your Expertise:

• 9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
• Strong programming (Python/Java) 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) and domains (eg. natural language processing, personalization and recommendation).
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive).
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
• Prior knowledge of ML Applications in the Payments domain is highly desirable

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.