Senior AI / Machine Learning Engineer — Fraud Detection
Core
Develop and broaden fraud and abuse detection systems using ML, data, and backend systems, applying LLMs and AI agents to real-time risk decisioning.
Role type
Senior hands-on IC machine learning engineer (fraud detection)
Builds
High-precision ML models, risk signals, and automated enforcement systems for fraud and abuse detection
Domain
Financial services / Risk management / Adversarial AI
Deliverable
production ML models
Required skills
Python, SQL, PyTorch, feature engineering, real-time system deployment, model monitoring, LLM integration, AI agent development, software/data engineering
Preferred skills
Device fingerprinting, identity verification, behavioral signals, network intelligence, distributed systems, high-scale data pipelines
Responsibilities
Build and deploy high-precision ML models for fraud detection; Engineer risk signals from large-scale account, device, and behavioral data; Integrate ML features into real-time risk decisioning; Apply LLMs and AI agents to expand detection capabilities; Translate emerging attack patterns into new models and mitigations; Evaluate solutions across accuracy, latency, and cost; Own model evaluation, monitoring, and drift management
Seniority
Senior, hands-on IC
