Senior Staff Machine Learning Engineer – GenAI

Airbnb

63d•Remote

About The Position

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

Requirements

Educational Background: PhD in Computer Science, Mathematics, Statistics, or related technical field.
Industry Experience: 10+ years of experience in building, testing and shipping AI models and products from inception to production; including 2+ years of experience with GenAI.
Leadership Experience: 10+ years experience leading and guiding machine learning and AI projects that deliver sizable impact as a senior IC.
Technical Proficiency: Deep knowledge and hands-on experience with Machine Learning best practices (eg. training/serving skew minimization, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. NLP, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection)

Nice To Haves

Agentic and Automation: Experience with AI technologies in automating processes and developing agentic solutions and frameworks.
Agile Practice for AI Production: Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain.
Infrastructure Acumen: Experience building robust testing frameworks for agent behavior validation and continuous improvement, and driving architectural requirements on ML infrastructures

Responsibilities

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.