Staff Machine Learning Engineer
Core
Architect and maintain end-to-end traffic classification ML systems to distinguish legitimate automation from abusive actors in real-time, hardening edge-traffic policies and reducing bot-incident MTTM.
Role type
Staff Machine Learning Engineer (Adversarial ML / Traffic Integrity)
Builds
Real-time traffic scoring models, offline-to-online data pipelines, and evaluation frameworks for bot mitigation at the internet edge.
Domain
Internet Security / Bot Mitigation / Adversarial Machine Learning
Deliverable
production ML models
Required skills
Production ML in adversarial domains, offline-to-online data pipeline architecture, rigorous model evaluation (ROC/AUC, calibration), large-scale data engineering (SQL), internet edge infrastructure knowledge, cross-functional leadership, mentoring
Preferred skills
PhD in Statistics/ML, graph-based coordination/Sybil detection, causal/econometric methods, Bayesian calibration, LLM agent tooling
Technologies
SQL, CDN, Load Balancers, HTTP/TLS, LLM agent tooling
Responsibilities
Own the complete lifecycle of traffic-scoring models from problem framing to real-time deployment, architect robust offline-to-online pipelines, execute model optimization within millisecond latency budgets, partner with security analysts and infrastructure teams, serve as the team's machine learning authority
Seniority
Staff, hands-on IC with strategic influence
