Gusto · 3 weeks ago
Staff Applied AI and Machine Learning Engineer, Payments & Risk
San Francisco Bay Area
Full-time
Hybrid
Lead/Staff
$225K/yr - $285K/yr
8+ years expGusto is on a mission to grow the small business economy by handling essential services like payroll and HR. They are seeking a technical leader to drive machine learning and AI initiatives in the payments and risk domains, focusing on building a model-driven risk platform to enhance user security and reliability.
Bookkeeping and PayrollEmployee BenefitsEnterprise SoftwareFinancial ServicesFinTechHuman ResourcesSaaSSoftware
Responsibilities
Build and deploy machine learning models to identify, assess and mitigate risks
Responsible for driving research in the problem space, working with stakeholders to understand model requirements, developing the model from scratch, deploying the model alongside your engineering counterparts, and monitoring and maintaining the model’s performance over time
Partner with Engineering, Design, and Product counterparts in Payment and Risk to solve complex cross functional problems
Develop scalable frameworks and libraries that enhance and contribute to the team’s core analysis and modeling capabilities, including through the integration of LLMs to improve data processing, analysis, and insights
Identify new opportunities to leverage data to improve Gusto’s products and help risk management team to understand business requirements and develop tailored solutions
Present and communicate results to stakeholders across the company
Qualification
Required
8+ years of experience conducting statistical analyses on large datasets and deep domain knowledge in machine learning and artificial intelligence, including familiarity with Large Language Models (LLMs) and their applications. This could mean either a MS or PhD in a quantitative field with at least 5 years experience in a business environment, or BS or Data Science Bootcamp graduate with at least 8 years of experience working as a data scientist or a machine learning engineer in a business setting
Proven experience in credit risk modeling or fraud risk modeling using logistic regression, random forest, Xgboost or neural networks, along with a strong understanding of AI-based approaches and the potential of LLMs to enhance traditional models
Experience applying a variety of statistical and modeling techniques using Python, R or another statistical modeling language, as indicated by familiarity with many of the following techniques - predictive modeling, anomaly detection, ensemble methods, natural language processing (NLP, optional). Basic understanding of LLMs and their applications
Strong programming skills - comfortable with all phases of the data science development process, from initial analysis and model development to deployment
Excellent communication skills - able to effectively deliver findings and recommendations to non-technical stakeholders in a clear and compelling fashion
Preferred
PhD or Masters plus equivalent experience in a quantitative field is a plus
Experience in the Fintech industry is a plus
Benefits
Health insurance
401(k)
Company
Gusto
Gusto is an HR and payroll platform that simplifies complex tasks, empowering businesses to focus on what matters most.
1001-5000 employees
H1B Sponsorship
Gusto has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (49)
2024 (54)
2023 (19)
2022 (37)
2021 (24)
Funding
Current Stage
Late StageTotal Funding
$746.1MKey Investors
Friends & Family CapitalT. Rowe PriceAkkadian Ventures
2023-01-28Series Unknown
2022-05-12Series E· $55M
2021-08-10Series E· $175M
Leadership Team
Josh Reeves
Head of Gusto (CEO) and Co-Founder. Building Gusto for the Long Term.
Edward Kim
Co-founder and Head of Technology
Recent News
General Catalyst
2025-12-30
Digital Commerce 360
2025-12-20
2025-12-19
Company data provided by crunchbase