Manager, Machine Learning Engineering (Fraud)

TL;DR

Manager, Machine Learning Engineering (Fraud): Leading a team of ML engineers to build and optimize fraud detection models with an accent on adversarial environments and complex behavioral data. Focus on defining technical strategy, driving the adoption of transformer-based techniques, and ensuring seamless integration of high-impact models into production decisioning systems.

Location: Remote (US only)

Salary: $204,000–$290,000 per year (depending on location)

Company

Affirm is a fintech company reinventing credit to provide consumers with flexible, transparent payment solutions without hidden fees.

What you will do

• Set the technical and modeling strategy for fraud detection to improve approval rates and reduce fraud loss.
• Lead and coach a team of machine learning engineers through the full ML lifecycle, from experimentation to production.
• Drive the evolution of modeling approaches, including the adoption of representation learning and transformer-based methods.
• Partner cross-functionally with Product, Analytics, Risk, and Engineering teams to define solutions and evaluate trade-offs.
• Foster a high-performing team culture grounded in technical excellence and ownership.

Requirements

• Must be based in the United States
• Bachelor’s degree in a technical field or equivalent practical experience.
• 8+ years of industry experience, including 3+ years in an engineering management role.
• Proven experience leading teams delivering end-to-end ML solutions in production environments.
• Strong expertise in modern ML approaches, including deep learning, transformers, and gradient-boosted trees.
• Solid engineering fundamentals with experience in scalable systems and data pipelines.

Culture & Benefits

• 100% subsidized medical, dental, and vision coverage for employees and dependents.
• Generous flexible spending wallets for technology, food, and lifestyle needs.
• Competitive vacation and holiday schedules.
• Employee stock purchase plan (ESPP) with discount.
• Remote-first work environment with occasional office collaboration.