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

Adobe; California (PA); Hybrid; USD 152,000 - 265,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Adobe is seeking a Senior AI/ML Engineer to build and evolve fraud detection systems. This hands‑on role spans ML, data, and backend work, with opportunities to apply LLMs and AI agents in detection and enforcement.

You will own end‑to‑end solutions from signals to deployment and real‑time decisions. The candidate will lead model evaluation, monitoring, and drift mitigation while collaborating with cross‑functional teams to ship production‑ready capabilities.

Qualifications

• 8+ years building production ML systems in fraud/risk domains.
• Strong Python, SQL and PyTorch experience.
• Experience guiding ML systems from features to production deployment and monitoring.
• Strong software/data engineering across ML/backend/data infra.
• Experience with LLMs/AI agents for abuse use cases.
• Bachelor's or equivalent in CS/Stats/Math; advanced degree a plus.

Responsibilities

• Build and deploy high‑precision ML models for fraud and abuse detection.
• Engineer risk signals from large‑scale account, device, network, behavioral data.
• Integrate ML features into real‑time risk decisioning and enforcement systems.
• Apply LLMs and AI agents to expand detection, investigation, and classification capabilities.
• Translate emerging attack patterns into new 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

Python

SQL

PyTorch

ML systems

LLMs / AI agents

Data engineering

Adversarial problem solving

Education

Bachelor's degree in Computer Science / Statistics / Mathematics

Advanced degree preferred

Job description

Adobe is seeking a Senior AI/ML Engineer to build and evolve fraud detection systems. This hands‑on role spans ML, data, and backend work, with opportunities to apply LLMs and AI agents in detection and enforcement.

You will own end‑to‑end solutions from signals to deployment and real‑time decisions. The candidate will lead model evaluation, monitoring, and drift mitigation while collaborating with cross‑functional teams to ship production‑ready capabilities.