Affirm is reinventing credit to make it more honest and friendly, giving consumers the flexibility to buy now and pay later without any hidden fees or compounding interest. The Fraud Machine Learning team builds models that power critical decisions during the loan application process, protecting the company and its customers from fraud while maintaining a seamless user experience. As a manager, you will lead a team of ML engineers developing and improving models that detect and prevent abuse in a rapidly evolving, adversarial environment. In this role, you will define the technical and modeling strategy for fraud detection, guiding the team across the full machine learning lifecycle from feature development and experimentation to production deployment and monitoring. You will partner closely with Product, Fraud Analytics, Risk, and Platform teams to ensure high‑quality models are effectively integrated into decision‑making systems. You will also help drive the evolution of modeling approaches at the company, including the adoption of representation learning and transformer‑based techniques to better capture complex behavioral patterns. What you’ll do Set the technical and modeling strategy for fraud detection, aligning team efforts with key business outcomes such as fraud loss reduction, approval rates, and customer experience Lead a team of machine learning engineers to design, build, and iterate on high‑impact fraud models across the full ML lifecycle, from experimentation to production Drive the evolution of modeling approaches, including the adoption of representation learning, transformer‑based methods, and other advanced techniques for modeling complex behavioral data Partner cross‑functionally with Product, Fraud Analytics, Risk, and Engineering to define solutions, evaluate trade‑offs, and ensure models are effectively integrated into decision‑making systems Develop talent by coaching engineers, providing feedback, and fostering a high‑performing team culture grounded in technical excellence and ownership What we look for Bachelor’s in a technical field with 8+ years of industry experience, including 3+ years managing engineers Experience with modern ML approaches, including representation learning, deep learning, or transformer‑based models, as well as traditional methods such as gradient‑boosted trees Proven ability to lead teams delivering end‑to‑end ML solutions in production environments, including experimentation, evaluation, and model iteration in production Strong engineering fundamentals and experience working with scalable systems and data pipelines Track record of effective cross‑functional collaboration with product, analytics, and engineering partners Ability to operate in ambiguous, fast‑evolving environments and drive clarity, prioritization, and execution This position requires either equivalent practical experience or a Bachelor’s degree in a related field Benefits Health care coverage – the company covers all premiums for all levels of coverage for you and your dependents Flexible Spending Wallets – generous stipends for spending on technology, food, various lifestyle needs, and family‑forming expenses Time off – competitive vacation and holiday schedules allowing you to take time off to rest and re‑charge Employee Stock Purchase Plan – an employee stock purchase plan enabling you to buy shares at a discount Compensation Pay Grade – 00 Equity Grade – 00 Employees new to the company typically come in at the start of the pay range. The company focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job‑related skills. Base pay is part of a total compensation package that may include monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, employees may be eligible for equity rewards offered by the parent company. CAN base pay range per year: $178,000 - $228,000 Remote Affirm is proud to be a remote‑first company! The majority of our roles are remote and you can work almost anywhere within the country of employment. Perform proximal roles may have limited office visits. A limited number of roles remain office‑based due to the nature of their responsibilities. We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process. Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, the company will consider for employment qualified applicants with arrest and conviction records. #J-18808-Ljbffr