Senior AI / Machine Learning Engineer, Fraud Prevention

What you'll do

• Build and deploy high-precision ML models for fraud detection, anomaly detection, and risk scoring.
• Engineer risk signals from large-scale account, device, network, behavioral, velocity, and session data.
• Integrate ML and AI features into real-time risk decisioning and automated enforcement systems.
• Apply LLMs and AI agents to expand detection, investigation, and classification capabilities.
• Translate emerging attack patterns and research into new models, signals, and mitigations.
• Own model evaluation, monitoring, and drift management as attacker behavior evolves.
• Evaluate solutions across accuracy, latency, cost, and customer impact metrics.

What we're looking for

• 8+ years of experience building and operating production ML systems, ideally in fraud, abuse, risk, or adversarial domains.
• Solid ML background with practical experience in Python, SQL, and current ML frameworks like PyTorch.
• Experience guiding ML systems from feature engineering to production deployment and monitoring.
• Strong software and data engineering skills across ML, backend, and data infrastructure.
• Experience building with LLMs and/or AI agents, particularly for AI/generation-abuse use cases.
• Bachelor's or equivalent experience in Computer Science, Statistics, Mathematics, or a related field.
• Advanced degree in a related field is a plus.
• Experience with device fingerprinting, identity verification, behavioral signals, or distributed systems (preferred).