Staff Machine Learning Engineer - Risk
Gusto · San Francisco, CA - Hybrid
About this role
**Staff Machine Learning Engineer - Risk** **About Gusto** At Gusto, we’re on a mission to grow the small business economy. We handle the hard stuff—payroll, health insurance, 401(k)s, and HR—so owners can focus on their craft and their customers. With teams in Denver, San Francisco, and New York, we support more than 500,000 small businesses nationwide and are building a workplace that reflects the people we serve. All full-time employees receive competitive base pay, benefits, and equity (RSUs). Learn more about our Total Rewards philosophy: https://gusto.com/about/careers/total-rewards AI is a fundamental part of how work gets done at Gusto. We expect team members to actively engage with AI tools relevant to their role and grow their fluency as the technology evolves. --- **About the Role** We’re looking for a technical leader (individual contributor) to drive machine learning and AI in the identity and risk domains. You’ll build a model-driven risk platform to provide a trusted environment for the Gusto ecosystem. You’ll work with an established team and seasoned leaders across Engineering, Product, Design, and Operations across Identity, Risk, and Compliance. You’ll build platforms spanning the Identity and Risk stacks, using ML/AI to create a world-class, high-secure platform that safeguards users’ activities and money—while ensuring reliability. --- **What You’ll Do (Day-to-Day)** - Build and deploy machine learning models to identify, assess, and mitigate risks - Drive research end-to-end: define requirements with stakeholders, develop models from scratch, deploy alongside engineering partners, and monitor/maintain performance over time - Partner cross-functionally with Engineering, Design, and Product in Identity and Risk to solve complex problems - Develop scalable frameworks and libraries to enhance core analysis/modeling capabilities, including integrating LLMs to improve data processing, analysis, and insights - Identify opportunities to leverage data to improve Gusto products and help the risk management team understand business requirements and develop tailored solutions - Present and communicate results to stakeholders across the company --- **What We’re Looking For** - 8+ years of experience conducting statistical analyses on large datasets, with deep domain knowledge in ML/AI (including familiarity with LLMs). Equivalent pathways include: - MS/PhD in a quantitative field + 5+ years in a business environment, **or** - BS or Data Science Bootcamp graduate + 8+ years working as a data scientist or ML engineer in a business setting - Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, XGBoost, or neural networks; strong understanding of AI-based approaches and how LLMs can enhance traditional models - Experience applying statistical and modeling techniques using Python, R, or similar languages (predictive modeling, anomaly detection, ensemble methods, optional NLP) - Strong programming skills across the data science lifecycle (analysis → model development → deployment) - Excellent communication skills; able to deliver findings and recommendations to non-technical stakeholders - PhD or Masters plus equivalent quantitative experience is a plus - Fintech experience is a plus --- **Compensation** Target cash compensation for this role is **$227k–$284k (San Francisco)**. Final offer amounts depend on multiple factors including experience and expertise. ---
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