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 ML Platform team is on a mission to build the core infrastructure that powers Affirm's intelligence. Affirm uses machine learning to assess and approve each BNPL transaction. Affirm’s ML models answer questions like: is the applicant willing and able to repay this loan?
The role of the ML Platform team is to build the compute platform for training and serving all of Affirm's ML models and features. Online, we operate a feature store and model server that enable real-time feature computation and model scoring. Offline, we manage an environment for running large scale model training and data analysis.
What You'll Do
· You will be responsible for owning and delivering quarterly goals for your team, leading engineers on your team through ambiguity to solve open-ended problems, and ensuring that everyone is supported throughout delivery.
· You will support your peers and stakeholders in the product development lifecycle by collaborating with product management, design & analytics by participating in ideation, articulating technical constraints, and partnering on decisions that properly consider risks and trade-offs.
· You will proactively identify project, process, technology or business issues, advocate for them, and lead in solving them.
· You will support the operations and availability of your team’s artifacts by creating and monitoring metrics, escalating when needed, and supporting “keep the lights on” & on-call efforts.
· You will foster a culture of quality and ownership on your team by setting or improving code review and design standards for your team, and advocating for them beyond your team through your writing and tech talks.
· You will help develop talent on your team by providing feedback and guidance, and leading by example.
What We Look For
· You have 4+ years of experience designing, developing and launching backend systems at scale using languages like Python or Kotlin.
· You have a track record of developing highly available distributed systems using technologies like AWS, MySQL and Kubernetes.
· You have experience defining a technical plan for the delivery of a significant feature or system component with an elegant, simple and extensible design. You write high quality code that is easily understood and used by others.
· You are proficient at making significant changes in a large code base, and have developed a suite of tools and practices that enable you and your team to do so safely.
· Your experience demonstrates that you take ownership of your growth, proactively seeking feedback from your team, your manager, and your stakeholders.
· You have strong verbal and written communication skills that support effective collaboration with our global engineering team.
· This position requires either equivalent practical experience or a Bachelor’s degree in a related field.
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: $190,000 - $240,000
USA base pay range (all other U.S. states) per year: $169,000 - $219,000
#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 and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
Top Skills
Affirm San Francisco, California, USA Office
650 California St, San Francisco, CA, United States, 94108
Similar Jobs at Affirm
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
