Staff ML Engineer - Edge Traffic & Bot Mitigation

airbnb, Inc.; Northern (KY); Hybrid; USD 180,000 - 270,000; Full time

Benefits offered by this job

Bonus eligibility

Equity

Employee Travel Credits

Job summary

Airbnb seeks a senior machine learning engineer to architect and maintain end-to-end traffic classification systems at the web edge, balancing latency with robust data pipelines. You will own the full lifecycle of models, collaborate with security, data platforms, and infra teams, and translate research into scalable engineering guidance for the organization.

The role emphasizes evasion-resistance, rigorous evaluation, and global collaboration to ensure consistent traffic classification across

Qualifications

• 9+ years in production ML within adversarial domains such as traffic integrity, bot mitigation, or fraud.
• Experience architecting scalable offline-to-online data pipelines.
• Rigorous model evaluation using ROC/AUC, calibration, and clear trade-offs.
• Proven cross-functional leadership delivering initiatives with data contracts.

Responsibilities

• Own the complete lifecycle of traffic-scoring models from framing to real-time deployment.
• Architect robust offline-to-online pipelines with certified datasets and evaluation checks.
• Optimize model latency at the edge within millisecond budgets while maintaining fail-safe behavior.
• Collaborate with security, data platform engineers, and infrastructure partners to unify scoring in mitigations.
• Translate complex research trade-offs into practical engineering guidance for leadership.

Skills

Production ML

Data pipelines

Model evaluation

SQL / data engineering

Edge infra

Leadership

Quant/PhD

Education

MS/PhD in quantitative field

Job description

Airbnb seeks a senior machine learning engineer to architect and maintain end-to-end traffic classification systems at the web edge, balancing latency with robust data pipelines. You will own the full lifecycle of models, collaborate with security, data platforms, and infra teams, and translate research into scalable engineering guidance for the organization.

The role emphasizes evasion-resistance, rigorous evaluation, and global collaboration to ensure consistent traffic classification across