Staff Machine Learning Engineer, Traffic Intelligence

Airbnb is a global hospitality and travel platform connecting hosts and guests through stays and experiences worldwide. The Staff Machine Learning Engineer will architect and maintain end-to-end traffic classification systems, including low-latency model deployment, offline-to-online data pipelines, and rigorous evaluation frameworks for detecting bots and abusive automated traffic. The role also provides technical leadership and partners cross-functionally to integrate scoring intelligence into global mitigation workflows.

Responsibilities:

• Own the complete lifecycle of traffic-scoring models, from problem framing to real-time deployment, managing the adversarial feedback loop to ensure high evasion-resistance and directly drive reductions in bot-incident MTTM
• Architect robust offline-to-online pipelines that produce certified source-of-truth datasets, establishing rigorous evaluation frameworks—such as stratified benchmarks and leakage-prevention checks—to ensure every model improvement is empirically measurable and defensible
• Execute model optimization within strict millisecond latency budgets at the internet edge, uniquely balancing inference costs against incremental value while maintaining fleet-wide fail-open behaviors
• Partner daily with security analysts, data platform engineers, and international infrastructure partners to integrate scoring intelligence into automated mitigation workflows, ensuring global consistency in traffic classification despite regional failovers or CDN updates
• Serve as the team’s machine learning authority, communicating complex model trade-offs to leadership and cross-functional teams to translate technical research into practical, scalable engineering guidance