Staff Machine Learning Engineer, Traffic Intelligence at Airbnb in United States

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: Our web and API surfaces handle requests from guests and hosts alongside a growing volume of automated agents: AI assistants, crawlers, and scrapers. We build the systems that bring clarity to this traffic, combining in-house ML and vendor signals to decide in real time how to serve billions of daily requests. Anti-bot and anti-scraping detection is our most adversarial mandate, but the wider challenge is full traffic classification: building evaluation frameworks that tell legitimate automation apart from abusive actors, so high-stakes decisions hold up across the fleet. The Difference You Will Make: You will architect and maintain Airbnb’s end-to-end traffic classification ML systems, balancing high-performance model deployment with rigorous offline data pipelines. Success is measured by your ability to harden edge-traffic policies—targeting reduced bot-incident MTTM—and by establishing rigorous evaluation practices that ensure foundational signal accuracy and evasion-resistance…