Manager, Machine Learning Engineering (Fraud)

Job Summary

The Fraud Machine Learning team at Affirm builds models that protect against fraud during the loan application process. As a manager, you will lead a team of ML engineers in designing, building, and iterating on high-impact fraud models. You will also drive the evolution of modeling approaches, including the adoption of advanced techniques like representation learning and transformer-based methods.

Responsibilities

• 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

Requirements

• 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
• Past experience leading 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
• Proven ability to collaborate effectively with product, analytics, and engineering partners
• Ability to operate in ambiguous, fast-evolving environments and drive clarity, prioritization, and execution

Qualifications

• Equivalent practical experience or a Bachelor’s degree in a related field

Benefits

• Competitive base pay range based on location, experience, and job-related skills
• Monthly stipends for health, wellness, and tech spending
• 100% subsidized medical coverage, dental, and vision for you and your dependents
• Flexible vacation and holiday schedules
• Employee stock purchase plan
• Remote-first work environment