Description
We are seeking a Staff Machine Learning Engineer to join our Traffic Intelligence team. You will play a critical role in architecting and maintaining Airbnb's end-to-end traffic classification ML systems, balancing high-performance model deployment with rigorous offline data pipelines.
The Difference You Will Make: Your primary objective will be to harden edge-traffic policies, targeting reduced bot-incident Mean Time To Mitigation (MTTM), and establish rigorous evaluation practices to 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 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.
- Serve as the team's machine learning authority, communicating complex model trade-offs to leadership and cross-functional teams.
Your Expertise:
- 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 that produce certified source-of-truth datasets for low-latency inference systems.
- 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 while mentoring junior engineers.
Preferred Qualifications:
- 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.
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.
How We'll Take Care of You: The base pay range for this role is $212,000-$265,000 USD. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.