Manager, Machine Learning Engineering (Underwriting)
Affirm
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Job Description
Join Affirm as a Machine Learning Engineering Manager and become a pivotal part of our innovative underwriting machine learning group. Specifically, you will manage a team of ML engineers that builds our economic decisioning engine, using novel ML techniques and rich representations of data to underwrite and optimize applications based on expected returns, lifetime value, and predicted conversion.
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.
- 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 to ensure technical sustainability, risks and trade-offs are well understood and managed.
- Develop talent by providing feedback and guidance, and leading by example.
- Bachelors in a technical field with 8+ years of industry experience, including 3+ years managing engineers
- 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.
- This position requires either equivalent practical experience or a Bachelor’s degree in a related field.
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: $230,000 - $290,000
USA base pay range (all other U.S. states) per year: $204,000 - $264,000
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.
Benefits
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
[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 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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