Machine Learning Engineering Manager, Affirm
Fraud
$200-275k
Salary dependent on location. + ESPP
Buy-now-pay-later card for online and in-store
Be an early applicant
Buy-now-pay-later card for online and in-store
1001+ employees
Be an early applicant
$200-275k
Salary dependent on location. + ESPP
1001+ employees
Company mission
To deliver honest and transparent financial products that improve users' lives.
Role
Who you are
- 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
What the job involves
- 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
- 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
Our take
Affirm offers point-of-sale loans to consumers, working with merchants like Shopify, KAYAK, and Walmart. Buy now, pay later transactions have grown in popularity in recent years, and this business is tapping into the market with a totally different approach to credit - by delivering the Affirm card, the first US debit card with the option to pay-over-time.
Serving over 21 million consumers and over 300,000 merchants, the company offers flexible payback options ranging from 3 to 36 months. The interest rates run between 0% and 30%, so, while they are not necessarily the cheapest option, Affirm prides itself on having no fees for late payments, no hidden charges, and total transparency about what people will pay before they take out a loan.
Affirm collects payments from the customers and pays the merchants directly, shouldering the risk itself. The company has boosted its market share, expanding its availability beyond the US to include most of Canada, and continues to launch new features and create new partnerships towards bettering its offering.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
-11% employee growth in 12 months
Company
Funding (last 2 of 5 rounds)
Sep 2020
$500m
SERIES G
Apr 2019
$300m
SERIES F
Total funding: $1.1bn
Company benefits
- Compensation: We have a simple, flexible, and transparent remote-first compensation structure so you can make the best decisions for yourself and your family
- Spending Wallets: Access tech, food, lifestyle, and family planning wallets for your expenses
- Supportive Communities: Get involved with our employee resource groups and community groups
- Remote-first Workforce: If your role is remote, you can set up shop anywhere in your home country
- Generous Time Off: Take the time you need when life happens
- Health Benefits: Get a plan that fits your needs
- Mental Healthcare: Take care of your mind with great mental health programs
- Parental Leave: Birth and non-birth parents get 18 weeks’ paid leave. Plus, a 4-week return-to-work transition program, at full base pay
- Away Days: We offer 20 company-wide paid days off—which help our teams collectively pause to recharge
- Learning & Development: Engage in exciting learning programs to level up your growth
Company HQ
Chinatown, San Francisco, CA
Leadership
Max Levchin
(Co-Founder & CEO)Has founded/co-founded numerous companies, holding various executive positions at each, including Paypal, Slide, Glow, HVF Labs, and SciFi VC. Also worked at large brands including Google, Yelp, Yahoo, and Evernote.
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