Staff Applied AI and Machine Learning Engineer, Payments & Risk at Gusto

This role is designed for a seasoned technical leader—an Individual Contributor—who specializes in high-stakes FinTech environments. While the listing mentions "Mid-level" seniority, the requirements (8+ years of experience and a "Staff" title) indicate they are looking for an expert capable of driving the machine learning strategy for credit and fraud risk. You should be comfortable with the full model lifecycle, from research and prototyping to deploying scalable frameworks in a business-critical production environment. The compensation is significant, reaching up to $285,000 in major hubs, plus the stability of working for a company serving over 400,000 businesses. Although the role is listed as "Remote," there is a clear hybrid expectation (2-3 days in-office) if you are based near their hubs in Denver, NYC, or SF. A major highlight is the opportunity to modernize risk stacks by integrating LLMs into traditional anomaly detection and predictive modeling workflows. **You might be a good fit if you...** * Have 8+ years of experience in ML engineering with a focus on fraud or credit risk. * Are an expert in Python and libraries like XGBoost, Random Forest, or Neural Networks. * Want to lead the integration of Generative AI/LLMs into risk management platforms. * Enjoy "full-stack" data science, moving between stakeholder meetings and production-level coding.