Staff Machine Learning Engineer, Traffic Intelligence

The posting, as Airbnb wrote it

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 across the fleet.

A Typical Day

• 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.

Your Expertise

• 9+ years of applied experience in production ML, specifically within non-stationary, adversarial domains (e.g., traffic integrity, bot mitigation, or fraud) where you have managed the feedback loop against adaptive actors.
• Demonstrated experience architecting scalable, offline-to-online data pipelines that produce certified source-of-truth datasets

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application.

Equal Employment Opportunity

Airbnb values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Airbnb are considered without regard to race, color, religion, national origin, age, gender, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, gender expression, sexual orientation, or any other legally protected characteristic.
How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range
$212,000 — $265,000 USD

Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @ airbnb.com or @ ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing. We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.