Upstart is the leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. By leveraging Upstart's AI marketplace, Upstart-powered banks and credit unions can have higher approval rates and lower loss rates across races, ages, and genders, while simultaneously delivering the exceptional digital-first lending experience their customers demand. More than 80% of borrowers are approved instantly, with zero documentation to upload. Upstart is a digital-first company, which means that most Upstarters live and work anywhere in the United States. However, we also have offices in San Mateo, California; Columbus, Ohio; and Austin, Texas. Most Upstarters join us because they connect with our mission of enabling access to effortless credit based on true risk. If you are energized by the impact you can make at Upstart, we’d love to hear from you! The Team: Upstart’s Verifications Decisioning team builds core capabilities that i) efficiently deliver online data sources for consumption by Machine Learning (ML) models to improve loan performance and ii) automate decisioning of applications using ML-driven rules to reduce friction and prevent fraud. Upstart has one of the lowest fraud rates in the industry and highest level of automation. This means that the majority of applicants can receive their funds in under 24 hours after they apply. Looking ahead, Verifications need to further push the boundaries of automation doubling down on initiatives that accelerate accuracy of ML models while extending those benefits beyond its flagship Personal Loans business to emerging products such as HELOC, Auto, and Small Dollar loans. As a Software Engineer at Upstart, you will build services to integrate with new data sources, implement and maintain highly scalable gRPC APIs for internal teams to access data, and partner closely with stakeholders to ensure data quality standards are met and ensured through thorough testing frameworks. These efforts will contribute in accelerating improvements to ML models using richer and more reliable data sources.