The Community You Will Join:

The Marketing Technology is focused on building the best-in-class platform and measurement capabilities to enable marketing and merchandising at Airbnb. We build products that are used by our stakeholders across the company including Marketing (Brand and Performance), Guest Experience, Host, Policy, and more. Our Mission is to enable both marketing and product teams to effectively deliver highly personalized and relevant marketing campaigns to the Airbnb community, both on-site and off-site.

The Difference You Will Make:

Personalization & Intelligence is one of the key focuses for the team moving into 2025 and beyond. As a Staff Machine Learning Engineer in Marketing Technology, you will make a big impact by leveraging AI/ML to enhance personalized customer experience at every step of the messaging journey - including content development, audience targeting, timing optimization, channel selection, and etc.  Projects will range from personalized listing/destination recommendations in marketing campaigns to future-oriented strategies on generative AI. 

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.
• Collaborate 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.
• Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable and high-performing Machine Learning systems. 

Your Expertise:

• 9+ years of industry experience in applied Machine Learning with a BS/Masters or 7+ years with a PhD
• 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) and algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization).
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Preferred Qualifications: Hands on experience with advanced Machine Learning Techniques, including but not limited to reinforcement learning, deep learning, and large language models (LLM).

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: reasonableaccommodations@airbnb.com. 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.