‍About the Role

Join us to design real-time fraud detection pipelines leveraging behavioral ML. You’ll work on keystroke dynamics, device entropy, and adversarial robustness in production-grade systems.

Responsibilities

• Build ML pipelines for fraud detection and session scoring.
• Engineer features for keystroke dynamics, device entropy, timing.
• Train/evaluate Random Forest, XGBoost, LightGBM with adversarial robustness.
• Keep FPR <3%, deliver explainable outputs via REST API.
• Monitor ML models continuously with signed deployment artifacts.

Requirements

• Strong Python ML skills (scikit-learn, XGBoost, LightGBM).
• Knowledge of adversarial ML, explainability, real-time scoring.
• Experience with containerized ML deployment.
• Bonus: cybersecurity/fraud detection background.