Manager, Machine Learning Engineering, Checkout Full Time NEW

Join Affirm as a Machine Learning Engineering Manager and become a pivotal part of our International Credit Machine Learning group. Specifically, you will manage a team of ML engineers that builds the models powering credit lending decisions in countries across Europe and in Australia. You will lead your team in using novel ML techniques and rich data representations to predict repayment behavior and optimize how we offer loans to our borrowers.

In this role, you will help shape the future of machine learning at Affirm. You'll partner with engineering, product, and risk leaders to design, implement, and scale advanced ML solutions that drive critical capabilities across the company. You will mentor engineers, bring clarity to complex, ambiguous problems, and contribute to a cohesive long-term ML strategy.

What you'll do

• Set the technical strategy for your team, and help your engineers tie it together with critical, business-impacting projects in our underwriting system
• Act as a force multiplier through your definition and advocacy of technical solutions and operational processes.
• Collaborate across teams in the product development lifecycle by partnering with product management, design, analytics, and risk to ensure technical sustainability, risks and trade-offs are well understood and managed.
• Develop talent by providing feedback and guidance, and leading by example.
• On-Call Rotation - There would be an on-call rotation for this role as a requirement.

What We Look For

• Bachelor's in a technical field with 8+ years of industry experience, including 3+ years managing engineers.
• A background in financial services, specifically in credit / lending.
• Proficiency in machine learning with experience in areas including tree-based models, transformers, deep learning, and agentic ML.
• Strong engineering skills and the ability to provide hands-on technical leadership while working with our code and architecture.
• You thrive in ambiguity, and are comfortable moving from low-level language idioms all the way to the architecture of large systems to understand how they work

Compensation & Benefits