Machine Learning Engineer
Core
Design and build end-to-end ML systems for real-time fraud detection and AML operations, integrating models with large-scale backend services.
Role type
Senior Machine Learning Engineer (Fraud Detection)
Builds
Production ML models, data pipelines, and backend services for fraud prevention
Domain
Financial crime, fraud detection, AML
Deliverable
production ML models
Required skills
Backend engineering (Go/Python), Applied ML (PyTorch/Scikit-learn), SQL, End-to-end ML systems design, Feature engineering, Model deployment and monitoring
Preferred skills
CI/CD, Docker, Kubernetes, Browser APIs, LLM automation
Technologies
Go, Python, PyTorch, Scikit-learn, SQL, Docker, Kubernetes
Responsibilities
Build and optimize data pipelines for real-time device and behavioral data processing; Develop and deploy ML models for fraud detection; Turn raw data into production-ready features; Collaborate with platform engineers to integrate models; Maintain security, privacy, and compliance standards; Champion testing, documentation, and observability best practices
Seniority
Senior, hands-on IC
