Machine Learning Engineer
Core
Build and deploy machine learning models to detect fraud, prevent abuse, and protect user experience across Adobe's products like Commerce, Stock, and Firefly.
Role type
Senior Machine Learning Engineer (Fraud Detection)
Builds
Real-time risk decisioning systems and unified trust/risk scores for hundreds of millions of users.
Domain
Financial services / Fraud detection / Behavioral modeling
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, scikit-learn, feature engineering, model lifecycle management, MLOps (experiment tracking, versioning, CI/CD), scalability, reliability, observability
Preferred skills
payment fraud, device fingerprinting, account takeover detection, anomaly detection, graph-based modeling, sequence modeling, transformer architectures, graph neural networks, Databricks, Spark
Responsibilities
Build and train ML models for financial transaction fraud, device deception, and identity abuse; contribute to feature engineering across transaction, device, and behavioral data; build and maintain feature pipelines on Databricks and Spark; translate prototypes into production ML systems; support MLOps practices; collaborate cross-functionally with data science, product, and platform teams.
Seniority
Senior, hands-on IC
