Manager, Machine Learning Engineering at Affirm

**Who this is for** An experienced technical manager who wants to lead a specialized team dedicated to protecting a financial platform through advanced machine

Work type: remote

Location: Remote US

Salary: $225,000 – $275,000/yr

Type: Full-time

Summary

**Who this is for** An experienced technical manager who wants to lead a specialized team dedicated to protecting a financial platform through advanced machine learning innovation. **Key highlights** You will define the strategy for fraud detection models, driving the adoption of cutting-edge techniques like transformer-based architectures to solve complex, adversarial behavioral challenges in real-time. **You might be a good fit if you...** - Have 8+ years of industry experience, including at least 3 years in a management capacity. - Possess hands-on experience with modern ML paradigms, including representation learning and deep learning. - Can successfully guide a team through the full ML lifecycle, from initial experimentation to high-impact production deployment. - Are a strong collaborator who can align technical modeling outcomes with critical business goals like fraud loss reduction.

Job Description

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.

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.

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.

What you’ll do

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

What we look for

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.

Pay Grade - P
Equity Grade - 13

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.

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.)

USA base pay range (CA, WA, NY, NJ, CT) per year: $225,000 - $275,000
USA base pay range (all other U.S. states) per year: $200,000 - $250,000

#LI-Remote

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.

We’re extremely proud to offer competitive benefits that are anchored to our core value of people come first. Some key highlights of our benefits package include:

Health care coverage - Affirm covers all premiums for all levels of coverage for you and your dependents

Flexible Spending Wallets - generous stipends for spending on Technology, Food, various Lifestyle needs, and family forming expenses

Time off - competitive vacation and holiday schedules allowing you to take time off to rest and recharge

ESPP - An employee stock purchase plan enabling you to buy shares of Affirm at a discount

We believe It’s On Us to provide an inclusive interview experience for all, including people with disabilities. We are happy to provide reasonable accommodations to candidates in need of individualized support during the hiring process.

[For U.S. positions that could be performed in Los Angeles or San Francisco] Pursuant to the San Francisco Fair Chance Ordinance and Los Angeles Fair Chance Initiative for Hiring Ordinance, Affirm will consider for employment qualified applicants with arrest and conviction records.

By clicking "Submit Application," you acknowledge that you have read Affirm's [Global Candidate Privacy Notice](https://www.affirm.com/global-candidate-privacy-notice) and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.

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