Machine Learning Engineer, Fraud

Tech Stack

Responsibilities

• Design, train, and deploy both traditional ML and LLM-powered models to detect fraudulent behaviors across users, payments, and marketplace interactions.
• Lead the end-to-end architecture of fraud detection, prevention, and intervention systems.
• Build intelligent user graphs to model behavioral patterns, collusion networks, and account connectivity.
• Develop scalable data pipelines and real-time inference systems supporting high-volume, low-latency ML workloads.
• Conduct deep behavioral and adversarial data analysis to uncover fraud trends and continuously improve detection accuracy.

Benefits

• 401k
• Gym Membership
• Health Insurance
• Parental Leave
• Remote Stipend
• Remote Work

Culture

Requirements