Manager, Machine Learning Engineering (Fraud)

Affirm

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$230,000–$290,000 / yr
Posted
49 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $227k
This role $260k
$168k most similar roles pay here $303k

This role pays more than 77% of similar roles. Most pay $195,000–$259,212 — the shaded band above. At the midpoint, this role pays about $260k versus about $227k for comparable roles.

Based on 240 similar postings.

Employer

About Affirm

Affirm is a buy-now, pay-later (BNPL) financial technology company that offers point-of-sale installment loans to consumers, allowing them to split purchases into fixed monthly payments with transparent terms. Industry: Financial Technology & Consumer Lending

Affirm currently has 57 open roles on FindRole.

Listed pay typically runs $195,000–$255,000 across 57 roles with salary data.

Most-posted roles

View all roles at Affirm

At a glance

TL;DR · Manager, Machine Learning Engineering (Fraud)

As a Manager of Machine Learning Engineering on the Fraud team, you will lead a senior-level team responsible for developing and enhancing machine learning models that detect and prevent fraud in loan applications. Your daily tasks include setting technical strategies, guiding model development from experimentation to production, and collaborating with cross-functional teams like Product, Risk, and Platform to integrate high-quality models into decision-making systems. You will also drive the adoption of advanced techniques such as representation learning and transformer-based methods to improve model accuracy. Ideal candidates have a Bachelor’s degree in a technical field, 8+ years of industry experience including at least 3 years managing engineers, expertise with modern ML approaches, strong engineering fundamentals, and proven success in leading teams through complex projects in ambiguous environments.

What you'll do

  • Define and implement the technical and modeling strategy for fraud detection.
  • Lead a team of ML engineers through the full lifecycle of model development from experimentation to production.
  • Adopt advanced techniques like representation learning and transformers in fraud models.
  • Collaborate with cross-functional teams to integrate high-quality models into decision systems.
  • Coach and develop engineering talent, fostering a culture of technical excellence.

What we're looking for

  • Bachelor’s degree in a technical field with 8+ years of industry experience, including 3+ years managing engineers.
  • Proven ability to lead teams delivering end-to-end ML solutions in production environments.
  • Experience with modern ML approaches like representation learning and transformer-based models.
  • Strong engineering fundamentals and experience with scalable systems and data pipelines.
  • Track record of effective cross-functional collaboration with product, analytics, and engineering partners.

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