Machine Learning Engineer (Traffic Classification)

Location

Location: Must live in a US state where Airbnb, Inc. has a registered entity. Remote eligible with occasional office or offsite attendance in the United States.

Company

Airbnb is a global platform founded in 2007, connecting millions of hosts and guests worldwide with unique stays and experiences.

What you will do

• Own the lifecycle of traffic-scoring ML models from problem framing to real-time deployment, ensuring evasion-resistance and reducing bot-incident MTTM.
• Architect offline-to-online data pipelines producing certified source-of-truth datasets and rigorous evaluation frameworks.
• Optimize models within strict millisecond latency budgets at the internet edge balancing inference cost and value.
• Collaborate with security analysts, data platform engineers, and infrastructure partners to integrate scoring intelligence globally.
• Serve as ML authority, communicating complex model trade-offs to leadership and cross-functional teams.

Requirements

• 9+ years of applied ML experience in adversarial domains such as bot mitigation or fraud.
• Experience architecting scalable offline-to-online data pipelines for low-latency inference.
• Strong foundation in rigorous model evaluation metrics and communication skills.
• Experience with large-scale data engineering and feature engineering on high-volume event streams.
• Practical knowledge of internet edge infrastructure like CDN and HTTP/TLS signatures.
• Must live in a US state where Airbnb has a registered entity.

Nice to have

• PhD in Statistics, Mathematics, Machine Learning, or related quantitative discipline.
• Expertise in graph-based coordination or Sybil network detection methods.
• Experience with causal or econometric methods for modeling business impact of false positives.
• Knowledge of Bayesian calibration techniques for adversarially-biased datasets.
• Familiarity with data governance and platform engineering for certified datasets.
• Exposure to LLM agent tooling and benchmarking focused on inference cost and latency trade-offs.

Culture & Benefits

• Remote eligible role with occasional office or offsite attendance.
• Competitive base pay with eligibility for bonus, equity, benefits, and employee travel credits.
• Commitment to inclusion, diversity, and disability-inclusive application process.