Senior Staff Machine Learning Engineer - Guest & Host

Details

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

The Users, Listings, and Marketplaces team supports features across the application related to Guests, Hosts and Listings. These products include 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 impact 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 involves close partnerships and influencing stakeholders across tech, product, and design to identify, scope, and deliver AI features. While you will be leading efforts with cross-functional stakeholders supported by a team of engineers, you’ll also be working hands-on to prototype, evaluate, and implement models.

Responsibilities

• 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 state-of-the-art models and prototype machine learning product features; 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.

Requirements / 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 Computer Science / Machine Learning or a related field.
• Strong programming skills (Python / Java / C++ or equivalent) with data and backend engineering expertise.
• Deep understanding of machine learning best practices (e.g., training/serving skew minimization, A/B testing, feature engineering, feature/model selection) and algorithms (e.g., 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 large, high-scale software applications (well-designed APIs, high-volume data pipelines, efficient algorithms and models).

Location & Work Arrangement

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed with your manager. While Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity (there is a continuously evolving list of excluded states). If employed by another Airbnb entity, your recruiter will inform you of state eligibility.

Compensation & Benefits

• Base pay range: $244,000 — $305,000 USD.
• This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. The actual base pay is dependent on factors such as training, transferable skills, work experience, business needs and market demands.

Inclusion & Accommodations

Airbnb is committed to working with the broadest talent pool possible and fostering inclusion and belonging. All qualified individuals are encouraged to apply. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, contact [email protected] with your full name, the role you’re applying for, and the accommodation necessary.