Senior Machine Learning Engineer

Role overview

This role focuses on developing and deploying machine learning solutions that help detect fraud, manage risk, and reduce financial losses. You will serve as a senior technical contributor in the risk and fraud domain, combining data analysis, statistical experimentation, production engineering, and close collaboration with operations teams to respond to changing threats.

Responsibilities

- Design, train, evaluate, and deploy machine learning models for risk assessment and fraud detection. - Provide technical direction for risk and fraud initiatives and help shape the team’s broader strategy. - Use SQL to retrieve, transform, and prepare data for analysis and model development. - Write reliable, maintainable, production-grade code for machine learning systems. - Apply statistical methods to design experiments, estimate sample sizes, and assess model performance. - Partner with operations teams to investigate and respond to rapidly evolving fraud and risk events.

Requirements

- At least five years of experience in data science or machine learning engineering. - Strong proficiency with Python and SQL. - Demonstrated experience developing and deploying machine learning models. - Excellent data analysis and problem-solving skills. - Ability to explain technical findings and decisions clearly to both technical and non-technical audiences.

Nice to have

- Experience with financial systems, lending, risk management, or fraud detection.

Benefits and work setup

- Remote-first position available within the United States, with an office option in Palo Alto, California. - The source describes health, dental, vision, life insurance, retirement matching, paid leave, holidays, flexible vacation, parental leave, and company-provided technology.