Senior AI/ML Engineer — Fraud Detection & Real-Time Risk

Adobe; Texas; Hybrid; USD 152,000 - 265,000; Full time

Job summary

Adobe is seeking a Senior AI/ML Engineer to build and operate fraud detection and abuse systems, applying anomaly detection, risk analysis, and AI/LLM-enabled capabilities. You will own end-to-end solutions from signals to production deployment and real-time decisioning, with impact across product, risk, and engineering teams.

The role blends hands-on ML, data, and backend work, requires 8+ years of production ML experience, strong Python/SQL and PyTorch skills, and a bias for ownership in a

Qualifications

• Production ML experience in fraud/risk/adversarial domains.
• Strong Python, SQL and PyTorch skills.
• Experience bringing ML systems from feature engineering to production deployment and monitoring.

Responsibilities

• Build and deploy high‑precision ML models for fraud and abuse detection, anomaly detection, and risk scoring.
• Engineer risk signals from large‑scale account, device, network, behavioral, velocity, and session data.
• Integrate ML/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 relevant research into new models, signals, and mitigations.
• Evaluate solutions across accuracy, latency, cost, and customer impact.
• Own model evaluation, monitoring, and drift as attacker behavior evolves.
• Partner across engineering, product, and risk teams to ship production‑ready capabilities.

Skills

Production ML systems

Python

SQL

PyTorch

LLMs / AI agents

Adversarial risk understanding

Ownership & accountability

Education

Bachelor's degree in CS/Statistics/Math

Tools

PyTorch

LLMs

Job description

Adobe is seeking a Senior AI/ML Engineer to build and operate fraud detection and abuse systems, applying anomaly detection, risk analysis, and AI/LLM-enabled capabilities. You will own end-to-end solutions from signals to production deployment and real-time decisioning, with impact across product, risk, and engineering teams.

The role blends hands-on ML, data, and backend work, requires 8+ years of production ML experience, strong Python/SQL and PyTorch skills, and a bias for ownership in a