Manager, Machine Learning Engineering (Fraud)

<div class="content-intro"><p>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.</p></div><p>&nbsp;</p> <p>The Fraud Machine Learning team builds models that power critical decisions during the loan application process, protecting Affirm 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.</p> <p>&nbsp;</p> <p>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 decisioning systems. You will also help drive the evolution of modeling approaches at Affirm, including the adoption of representation learning and transformer-based techniques to better capture complex behavioral patterns.</p> <p><br>What you’ll do</p> <ul> <li> <p>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</p> </li> <li> <p>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</p> </li> <li> <p>Drive the evolution of modeling approaches, including the adoption of representation learning, transformer-based methods, and other advanced techniques for modeling complex behavioral data</p> </li> <li> <p>Partner cross-functionally with Product, Fraud Analytics, Risk, and Engineering to define solutions, evaluate trade-offs, and ensure models are effectively integrated into decisioning systems</p> </li> <li> <p>Develop talent by coaching engineers, providing feedback, and fostering a high-performing team culture grounded in technical excellence and ownership</p> </li> </ul> <p><br>What we look for</p> <ul> <li> <p>Bachelor’s in a technical field with 8+ years of industry experience, including 3+ years managing engineers</p> </li> <li> <p>Experience with modern ML approaches, including representation learning, deep learning, or transformer-based models, as well as traditional methods such as gradient-boosted trees</p> </li> <li> <p>Proven ability to lead teams delivering end-to-end ML solutions in production environments, including experimentation, evaluation, and model iteration in production</p> </li> <li> <p>Strong engineering fundamentals and experience working with scalable systems and data pipelines</p> </li> <li> <p>Track record of effective cross-functional collaboration with product, analytics, and engineering partners</p> </li> <li> <p>Ability to operate in ambiguous, fast-evolving environments and drive clarity, prioritization, and execution</p> </li> <li> <p>This position requires either equivalent practical experience or a Bachelor’s degree in a related field.</p> </li> </ul> <p><br>Pay Grade - P<br>Equity Grade - 13<br><br>Employees new to Affirm typically come in at the start of the pay range. Affirm focuses on providing a simple and transparent pay structure which is based on a variety of factors, including location, experience and job-related skills.<br><br>Base pay is part of a total compensation package that may include equity rewards, monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents.)<br><br>USA base pay range (CA, WA, NY, NJ, CT) per year: $225,000 - $275,000<br>USA base pay range (all other U.S. states) per year: $200,000 - $250,000<br><br>#LI-Remote</p><div class="content-conclusion"><div> <p>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. Affirmers in proximal roles have the flexibility to work remotely, but will occasionally be required to work out of their assigned Affirm office. A limited number of roles remain office-based due to the nature of their job responsibilities.</p> <p><span style="font-weight: 400