Engineering Manager - Machine Learning
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.
We are looking for a staff level software engineer to lead our platform efforts in machine learning. You will be a technical leader within the engineering team, leading a team of engineers in developing an integrated system to support offline research, feature engineering, and model development, as well as robust and reliable execution of online decision systems. As a member of the Risk Engineering team, you will work closely with data scientists in our Risk and Analytics organization to build, test, deploy, and maintain software that enables them to work more efficiently and effectively.
What you will do
- Designing and developing machine learning systems that support our identity verification, fraud detection, credit underwriting, and servicing functions
- Testing and validation systems for data pipelines, business logic, and decision models
- Research and develop tools enabling our data scientists to efficiently and safely develop, test, and deploy experimental and production signals, models, and policies
- Effectively planning, coordinating, and communicating within the team, and cross-functionally
What We Look For
- Passion and drive to change consumer banking for the better
- 7+ years industry experience
- Strong proficiency and industry experience building and leading the development of production-quality machine learning systems
- Solid engineering and software development skills - ability to write, test, deploy, and maintain high-quality production code
- Deep understanding of models, feature engineering, feature selection, and other applied ML issues
- Experience in Python, or other dynamically typed language, is a plus
- Engineering management experience is a plus
- Finance and credit experience is a plus
At Affirm, people come first is a core company value and that’s why Diversity & Inclusion are vital to our priorities as an equal opportunity employer. You can learn more about our D&I efforts here.
We also consider qualified applicants with arrest and conviction records for positions in accordance with applicable laws, including the San Francisco Fair Chance Ordinance.
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