Hybrid ML Engineer: Fraud & Dispute Modeling

Location

This is a hybrid role based out of our San Francisco, CA or New York, NY office. Our team works in-office time on Mondays, Wednesdays, and Fridays.

• Develop and implement machine learning models to evaluate disputes and chargebacks and likelihood of fraud
• Create and manage an orchestration layer for multiple models, enabling automated and supervised decision‑making processes
• Collaborate with stakeholders to leverage valuable data from partners and customers, ensuring a continuously learning experience and first‑class user experience

• 3+ years of experience designing and deploying ML models in a high‑scale production environment
• Strong knowledge of machine learning algorithms and data analysis techniques
• Enthusiastic about building ML infrastructure from scratch in a nascent environment
• Ability to think like a product engineer, balancing technical innovation with practical application and user needs.
• Strong proficiency in programming languages like Python, R, or similar, and experience with ML frameworks like Tensor Flow, PyTorch, or scikit‑learn
• Excellent problem‑solving skills and the ability to work independently and in a collaborative team environment