Senior Machine Learning Engineer - Fraud

Responsibilities

• Research and prototype advanced approaches across graph machine learning, sequential modeling, and multimodal learning for fraud detection.
• Own and execute a research roadmap that turns innovative ideas and prototypes into production solutions with measurable product and customer impact.
• Design rigorous experiments and evaluation methodologies reflecting real-world fraud dynamics.
• Partner with Machine Learning Engineers and cross-functional teams to translate research into production-ready systems.
• Publish and communicate applied research findings internally and externally.

Requirements

• PhD in Machine Learning, Artificial Intelligence, Computer Science, Statistics, Applied Mathematics, or a closely related field is strongly preferred.
• Candidates without a PhD may qualify through equivalent research experience, including significant publications, patents, or widely adopted research contributions.
• At least 2–4+ years of relevant industry or research lab experience, ideally post-PhD, with demonstrated research leadership and measurable product or business impact.
• Strong scientific rigor and written and verbal communication skills.
• Strong proficiency in Python and experience building high-quality research prototypes that can transition into production systems.
• Experience in fraud detection, security, risk, abuse prevention, large-scale training, graph systems, or sequential modeling is preferred.

Benefits

• Comprehensive medical, dental, vision, and 401(k) benefits.
• Additional equity and/or commission may be provided depending on the position offered.