Senior Staff Machine Learning Engineer – GenAI

airbnbUnited Statesgreenhouse
Posted Date:

September 8, 2025

Employment Type:

Not specified

Work Arrangement:

On-site/Hybrid

Skills & Technologies

Software Engineeringpreferred

Job Description

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.

Community you will join

At Airbnb, we’re reimagining how support is delivered at a global scale. The Community Support Engineering (CSE) team is leading a multi-year transformation—building intelligent, AI-augmented systems that provide timely, personalized, and always-on support experiences for our global community.

The CS Foundations Engineering (CSFE) team powers this mission by delivering robust platforms, reusable systems, and developer-facing infrastructure. Our tools help agents deliver exceptional service, enable faster product iteration, and support Airbnb’s mission to create a world where anyone can belong anywhere—with help that’s just a moment away.

The Difference You Will Make:

    • As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered solutions to shape the future of the Airbnb customer experience with cutting-edge AI techniques. You will drive and guide the rest of the engineers to brainstorm, design and develop AI products and features from inception to production.
    • We're seeking a Senior Staff Engineer who thrives at the intersection of technical depth, architectural thinking, and mentorship.
    • You’ll collaborate with cross-functional leaders, build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered customer support.

While this role won’t own every project below, the below showcase the breadth and depth of work across our group, and where your leadership may be needed:

    • Building a unified, platform-native case management system (AirCase), abstracted via Viaduct APIs and replacing legacy CRM systems.
    • Designing scalable AI workflow orchestration to power agent co-pilot tools and intelligent response automation.
    • Modernizing our Delivery Management Console (DMC) to include AI powered real-time performance insights, outlier detection, and agent coaching tools.
    • Establishing shared data foundations to enable AI/ML solutions, feedback loops, and personalization across the support journey.
    • Delivering next generating matching capabilities (Routing) so incoming customer contacts are matched to the best agents using AI and Intelligence to deliver personalized and differentiated support experiences

A Typical Day:

    • Work with large scale structured and unstructured data; explore, experiment, build and continuously improve Machine Learning models and pipelines for Airbnb product, business and operational use cases.
    • Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions.
    • 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, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.
    • Collaborate actively with engineers to apply ML / AI in their solutions to help validate ideas and guide to the right outcomes.
    • Partner with other ML Engineers in foundations engineering to mentor and develop initiative to make ML application a core discipline for non ML engineers.

Minimum Qualifications:

  • Educational Background: PhD in Computer Science, Mathematics, Statist