Affirm is seeking to transform the credit industry by making it more transparent, honest, and consumer-friendly, and the Machine Learning Engineer role will be instrumental in managing and optimizing the flow of loan opportunities across Affirm-owned properties to balance unit economics, product growth, and user experience.
Requirements
- Proficiency in machine learning techniques including Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration
- Domain knowledge in credit risk, portfolio management, learning to rank, and personalization is a plus
- Strong engineering skills in Python and data manipulation skills in SQL
- Experience delivering major system features, components, or deprecating existing functionality with well-defined technical and execution plans
- Ability to write high-quality, maintainable, and scalable code
- Comfortable working across the full spectrum from low-level language idioms to large system architecture
- Proven track record of gathering and iterating on feedback from engineering and cross-functional peers to drive impact
Responsibilities
- Define and execute the technical strategy for your team on an annual basis, aligning with business goals and product roadmap
- Collaborate with product management, design, and analytics teams to develop scalable and sustainable ML solutions
- Act as a technical leader by advocating for best practices, standards, and operational excellence in code quality and system design
- Ensure operational reliability by implementing monitoring, triage procedures, testing, and alerting systems to support “keep the lights on” efforts
- Foster a culture of ownership, quality, and continuous improvement within your team
- Lead code reviews, design discussions, and technical documentation to promote knowledge sharing and best practices
- Participate in cross-functional projects to deliver impactful features and improvements in portfolio management
Other
- Bachelor’s degree in a technical field such as Computer Science, Data Science, or related discipline; relevant PhD can count for up to 2 years of experience
- 8+ years of industry experience in machine learning, data engineering, or related fields
- Excellent verbal and written communication skills, capable of collaborating effectively with global teams
- Equivalent practical experience or a related degree is acceptable
- Ability to work in a remote-first organization with a dynamic and inclusive work environment
