Senior AI / Machine Learning Engineer, Fraud Detection

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 mitigation strategies.
• Manage model evaluation, monitoring, and drift as attacker behaviors evolve.
• Evaluate technical solutions based on accuracy, latency, cost, and customer impact.

What we're looking for

• 8+ years of experience building and operating production ML systems in fraud, abuse, risk, or adversarial domains.
• Proficiency in Python, SQL, and modern ML frameworks like PyTorch.
• Experience managing the full ML lifecycle from feature engineering to production deployment and monitoring.
• Strong software and data engineering skills across backend and data infrastructure.
• Experience building with LLMs and/or AI agents for detection or investigation use cases.
• Bachelor's degree in Computer Science, Statistics, Mathematics, or a related field (advanced degree preferred).
• Expertise in device fingerprinting, identity verification, or network intelligence (preferred).
• Experience with distributed systems, high-scale data pipelines, and real-time risk evaluation (preferred).