[Hiring] Staff Machine Learning Engineer, Traffic Intelligence @Airbnb

Role Description

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.
• The wider challenge is full traffic classification: building evaluation frameworks that tell legitimate automation apart from abusive actors.

The Difference You Will Make:

• You will architect and maintain Airbnb’s end-to-end traffic classification ML systems.
• Success is measured by your ability to harden edge-traffic policies—targeting reduced bot-incident MTTM.
• Establish 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.
• Manage 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.
• Establish rigorous evaluation frameworks—such as stratified benchmarks and leakage-prevention checks.
• Execute model optimization within strict millisecond latency budgets at the internet edge.
• Partner daily with security analysts, data platform engineers, and international infrastructure partners.
• Serve as the team’s machine learning authority, communicating complex model trade-offs to leadership and cross-functional teams.

Qualifications

• 9+ years of applied experience in production ML, specifically within non-stationary, adversarial domains (e.g., traffic integrity, bot mitigation, or fraud).
• Demonstrated experience architecting scalable, offline-to-online data pipelines.
• Strong foundation in rigorous model evaluation, including metrics like ROC/AUC, precision/recall, and calibration.
• Experience with large-scale data engineering (warehouse-scale SQL) and feature engineering on high-volume event streams.
• Practical knowledge of internet edge infrastructure (e.g., CDN/load balancer behavior, HTTP/TLS signatures).
• Proven track record of cross-functional leadership, landing initiatives through shared datasets and consumer contracts.
• MS/PhD in a quantitative field (e.g., Statistics, ML) or equivalent deep engineering experience.

Requirements

• Preferred: PhD in Statistics, Mathematics, Machine Learning, or a related quantitative discipline.
• Advanced expertise in graph-based coordination or Sybil network detection methods.
• Deep experience with causal or econometric methods to model the business impact of false positives on legitimate user traffic.
• Experience implementing Bayesian calibration techniques for handling adversarially-biased, sparse, or imbalanced datasets.
• Familiarity with data governance practices and platform engineering.
• Exposure to LLM agent tooling and benchmarking.

Location

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity.

Our Commitment To Inclusion & Belonging

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected].

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