Senior Manager, Machine Learning - Small Dollar Loans & Cash Line

Upstart
United States | RemoteUp to $15kPosted 19 March 2026

Job Description

About Upstart At Upstart, we’re united by a mission that matters: to radically reduce the cost and complexity of borrowing for all Americans. Every day, we bring creativity, experimentation, and advanced AI to reshape access to credit, helping millions move forward financially with clarity and confidence. As the leading AI lending marketplace, we partner with banks and credit unions to expand access to affordable credit through technology that’s both radically intelligent and deeply human. Our platform runs over one million predictions per borrower using more than 1,800 signals, powering smarter, fairer decisions for millions of customers. But the numbers only hint at the impact. Every idea, every voice, and every contribution moves us closer to a world where credit never stands between people and their financial progress. We’re proudly digital-first, giving most Upstarters the flexibility to do their best work from wherever they thrive, alongside teammates across 80+ cities in the US and Canada. Digital-first doesn’t mean distant. We’re intentional about in-person connection through team onsites, planning sessions, and moments that spark creativity and trust. And whether you choose to work primarily from home or collaborate in-person from one of our offices in Columbus, Austin, the Bay Area, or New York City (opening Summer 2026), you’ll have the support to work in the way that works best for you. If you’re energized by tackling meaningful problems, excited to innovate with purpose, and motivated by work that truly matters, we’d love to hear from you. The Team Upstart’s Small Dollar Loans (SDL) and Cash Line ML teams sits at the center of our mission to expand access to credit for those who need it most. SDL provides short-term personal loans; Cash Line, our soon-to-launch subscription-based line of credit, offers ongoing flexibility for customers often left out of traditional lending. Both products aim to ease financial strain and improve long-term outcomes for underserved borrowers. This high-performing team of scientists and engineers, soon to be led by you, builds and refines the core underwriting and pricing models behind these products. These are Upstart’s most innovative and experimental systems - applying ML not only to predict credit risk but also to optimize the costs of lending so we can expand approvals while keeping borrowing affordable. You’ll advance these systems end-to-end: improving risk separation, refining cost models, and designing the decision logic that translates model outputs into customer-facing decisions. You’ll also lead 0→1 efforts that establish new ML capabilities, particularly for Cash Line. You’ll collaborate closely with GMs, Product, and Engineering to drive these products from experimentation to scale. How you'll make an impact: Drive early ML innovation for Cash Line , developing and refining our first suite of models for customer behavior (churn, draw, graduate, default) Improve and evolve SDL underwriting models and efficiency , and explore convergence opportunities with personal loan models to ensure a unified, scalable approach to small-dollar credit Design or refine decision engines that translate model predictions into accurate, transparent, and customer-friendly lending outcomes Develop and validate robust model performance metrics that build confidence in our systems and unlock resilient, low-cost capital from investors Foster a culture of technical rigor, fast learning, and pragmatic execution within a small, high-talent team operating at the frontier of Upstart’s lending innovation Collaborate closely with Product, Engineering, Capital Markets, and Data Analytics to align ML solutions with product strategy, business goals, and financial performance. Attract, mentor, and grow a top-tier team of ML scientists passionate about expanding access to credit. What we're looking for: Minimum Qualifications Experience 6+ years of experience developing and deploying ... (truncated, view full listing at source)
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