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.
Join Affirm’s ML Fraud team as a Machine Learning Engineer II and advance our capabilities in detecting and preventing online fraud. Leverage cutting-edge algorithms and proprietary data to outsmart fraudsters while ensuring seamless experiences for genuine customers. Your work will directly impact Affirm's financial performance by developing sophisticated models for real time transaction decisions.
Collaborate with experts to tackle complex challenges, create innovative solutions for emerging fraud patterns, and advance our fraud detection capabilities. If you're passionate about machine learning, thrive on challenges, and want to make a tangible difference in fintech, Affirm is your opportunity. Help us create honest financial products that improve lives while growing your career in a dynamic, impactful environment.
Use Affirm’s proprietary and other third party data to develop machine learning models that predict the likelihood of fraud. These models will protect victims’ identities from being stolen, prevent Affirm from incurring financial loss, and increase the trust that consumers and partners have in the Affirm ecosystem.
Partner with the ML platform team to build fraud specific ML infrastructure
Research ground breaking solutions and develop prototypes that drive the future of fraud decisioning at Affirm
Implement and scale data pipelines, new features, and algorithms that are essential to our production models
Collaborate with the engineering, fraud, and product teams to define requirements for new products
Develop fraud models to maximize user conversion while minimizing fraud losses and data costs.
2+ years of experience as a machine learning engineer or PhD in a relevant field
Proficiency in machine learning with experience in areas such as gradient boosting, online learning, and deep learning. Domain knowledge in fraud risk is a plus
Strong programming skills in Python
Experience using large scale distributed systems like Spark and Ray
Experience using machine learning frameworks such as scikit-learn, pandas, numpy, xgboost, and pytorch
Excellent written and oral communication skills and the capability to drive cross-functional requirements with product and engineering teams
The ability to present technical concepts and results in an audience-appropriate way
Persistence, patience and a strong sense of responsibility – we build the decision making that enables consumers and partners to place their trust in Affirm!
Base Pay Grade - L
Equity Grade - 5
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 monthly stipends for health, wellness and tech spending, and benefits (including 100% subsidized medical coverage, dental and vision for you and your dependents). In addition, the employees may be eligible for equity rewards offered by Affirm Holdings, Inc. (parent company).
CAN base pay range per year: $125,000 - $175,000
#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:
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 the Affirm Employment Privacy Policy for applicants within the United States, the EU Employee Notice Regarding Use of Personal Data (Poland) for applicants applying from Poland, the EU Employee Notice Regarding Use of Personal Data (Spain) for applicants applying from Spain, or the Affirm U.K. Limited Employee Notice Regarding Use of Personal Data for applicants applying from the United Kingdom, and hereby freely and unambiguously give informed consent to the collection, processing, use, and storage of your personal information as described therein.
