Who you are

• 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

What the job involves

• 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 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
• 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 decisioning systems
• Develop talent by coaching engineers, providing feedback, and fostering a high-performing team culture grounded in technical excellence and ownership

Benefits

• Compensation: We have a simple, flexible, and transparent remote-first compensation structure so you can make the best decisions for yourself and your family
• Spending Wallets: Access tech, food, lifestyle, and family planning wallets for your expenses
• Supportive Communities: Get involved with our employee resource groups and community groups
• Remote-first Workforce: If your role is remote, you can set up shop anywhere in your home country
• Generous Time Off: Take the time you need when life happens
• Health Benefits: Get a plan that fits your needs
• Mental Healthcare: Take care of your mind with great mental health programs
• Parental Leave: Birth and non-birth parents get 18 weeks’ paid leave. Plus, a 4-week return-to-work transition program, at full base pay
• Away Days: We offer 20 company-wide paid days off—which help our teams collectively pause to recharge
• Learning & Development: Engage in exciting learning programs to level up your growth