Senior Staff Machine Learning Engineer - Guest & Host

The Community You Will Join:

The Users Listings and Marketplaces team supports features across the application related to Guests Hosts and Listings. These products include but are not limited to management tools for listings enforcement/quality systems and merchandising systems. The team works closely with product and design to ship highly visible product functionality and drive innovation within the product.

The Difference You Will Make:

There is huge potential for AI to how guests book and how Hosts manage listings at Airbnb. You will improve the Guest and Host experience by improving the intelligence of our product through state of the art machine learning models. This will involve close partnerships and influencing stakeholders across tech product and design organizations to identify scope and deliver AI features. While you will be leading efforts with XFN stakeholders supported by a team of engineers you’ll also be working hand in hand with the team to prototype evaluate and implement models.

A Typical day:

Your contributions take a variety of shapes:

• Leverage structured and unstructured data to build and continuously improve state of the art Machine Learning models for Airbnb product business and operational use cases.

• Work collaboratively with engineers product managers data scientists and operations to identify problems and deploy ML capabilities.

• Stay up to date with SoT models and prototype machine learning product features and iterate with product and design.

• Drive best practices develop playbooks and create a repeatable process for shipping quality machine learning features.

• Hands-on development productionization and maintenance of machine learning models and pipelines at scale.

Your Expertise:

• Industry experience building and shipping end to end machine learning features

• 12+ years of industry experience in applied Machine Learning with experience in both Natural Language Processing and Computer Vision

• A Bachelor’s Master’s or PhD in CS/ML or related field

• Strong programming (Python / Java/ C++ or equivalent) skills with data and backend engineering expertise

• 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)

• Experience with technologies such as: Tensorflow PyTorch Kubernetes Airflow (or equivalent) Kafka (or equivalent)

• Expertise with architectural patterns of a large high-scale software applications (e.g. well-designed APIs high volume data pipelines efficient algorithms models)

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.