Affirm is looking to transform the credit industry by making it more honest and user-friendly, and the Senior Machine Learning Engineer role is instrumental in shaping the technical strategy for portfolio management models that optimize loan opportunities across Affirm's platforms.
Requirements
- Proficiency in machine learning techniques such as 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 programming skills in Python and data manipulation expertise in SQL
- Experience delivering major features and system components, including deprecation of existing functionalities
- Ability to write high-quality, maintainable, and scalable code
- Comfortable working across the full spectrum of system architecture, from low-level language idioms to large-scale system design
- Experience with machine learning and software engineering
Responsibilities
- Define and execute the technical strategy for portfolio management models aligned with business goals
- Develop and advocate for scalable, sustainable, and innovative technical solutions
- Ensure operational excellence by implementing monitoring, triage, testing, and alerting mechanisms
- Establish and uphold code review and design standards to maintain high-quality engineering practices
- Lead initiatives to improve system reliability, scalability, and performance
- Mentor and develop engineering talent through feedback, guidance, and leading by example
- Participate in technical discussions, knowledge sharing, and technical talks within the organization
Other
- Bachelor’s degree in Computer Science, Engineering, or a related technical field
- 8+ years of industry experience in machine learning and software engineering; relevant PhD can count for up to 2 years of experience
- Excellent verbal and written communication skills, supporting effective collaboration with global teams
- Proven track record of gathering and iterating on feedback to improve technical solutions and team performance
- Equivalent practical experience or a related bachelor’s degree is acceptable
