Machine Learning Engineer
Core
Design and deploy end-to-end ML systems for real-time fraud detection and AML operations, integrating modeling with large-scale backend services.
Role type
Senior Machine Learning Engineer (Fraud Detection)
Builds
Production ML models, data pipelines, and backend services for fraud detection systems
Domain
Financial crime, fraud prevention, AML
Deliverable
production ML models
Required skills
Backend engineering (Go/Python), Applied ML (PyTorch/Scikit-learn), SQL, End-to-end ML systems, Feature engineering, Model deployment, Monitoring
Preferred skills
CI/CD, Docker, Kubernetes, Browser APIs, High-entropy data collection, LLMs for automation
Technologies
Go, Python, PyTorch, Scikit-learn, SQL, Docker, Kubernetes
Responsibilities
Build and optimize data pipelines and backend services for real-time 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
