Machine Learning Engineer
Core
Build and deploy machine learning models to detect fraud, abuse, and deceptive behavior across Adobe's products, protecting hundreds of millions of users in real-time.
Role type
Senior IC machine learning engineer (fraud detection)
Builds
Production ML systems for risk scoring, feature pipelines, and model monitoring
Domain
Fintech / Cybersecurity / Fraud Detection
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
Technologies
Databricks, Spark, PyTorch, TensorFlow, scikit-learn
Responsibilities
Build and train ML models for financial transaction fraud, device deception, and identity abuse; engineer features from transaction, device, and behavioral data; maintain feature pipelines; translate prototypes to production systems; support MLOps practices; collaborate cross-functionally on fraud patterns.
Seniority
Senior, hands-on IC
