The opportunity
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…
What you'll do
Define and execute on the long-term ML technical vision and strategy for the: Trust organization, identifying key investments, architecting scalable solutions, and championing best practices that advance the state-of-the-art in production ML systems.
Serve as a technical leader and mentor to other ML and software engineers: across the organization, providing guidance on complex architectural and modeling challenges, and raising the overall technical bar.
Drive and deliver large-scale, multi-quarter ML initiatives that span: multiple teams, influencing roadmaps and ensuring alignment between platform and product
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.
Work collaboratively 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.
Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks.
What they're looking for
- Hands-on develop, productionize, and operate Machine Learning models and: pipelines at scale, including both batch and real-time use cases.
- Examples include: Anomaly detection models, ML models for continuous risk evaluation, Multimodality and Agentic AI
- + years of industry experience in applied Machine Learning
- + years working with LLMs and novel GenAI technologies. Proficiency and: proven experience on Agentic AI (frameworks, orchestration, architecture and productionization).
