Machine Learning Engineer

Job Summary

Seeking a remote Machine Learning Engineer specializing in fraud, the successful candidate will design, build, and deploy end-to-end machine learning systems to combat payments fraud and risk, while collaborating with cross-functional teams to translate real-world fraud patterns into actionable modeling solutions.

Key Responsibilities

• Design, build, and ship end-to-end ML systems for payments fraud and risk, including data pipelines and models
• Develop and productionize models using various techniques, including tree-based and neural architectures
• Analyze the payments ecosystem to identify new attack vectors and opportunities for protective products

Required Qualifications

• Significant experience as an Applied Scientist or Machine Learning Engineer building production ML systems
• Strong coding skills in a production language such as Python, Ruby, or Go
• Deep hands-on experience with tree-based models and neural architectures for sequences
• Track record of owning end-to-end ML solutions from data exploration to deployment
• Experience operating in adversarial domains such as fraud, risk, or trust & safety