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Salary: CAD 133,000 - 183,000 / annual
Affirm is seeking a Machine Learning Engineer II to develop production-ready machine learning models that drive credit decisioning and risk assessment. You will work on high-impact problems in financial services, building models that predict default likelihood and inform approval/decline decisions.
Key Responsibilities:
- Develop machine learning models using Affirm's proprietary and third-party data to predict default risk and support business objectives
- Partner with platform and product engineering teams to build model training, decisioning, and monitoring systems
- Research and prototype breakthrough solutions for credit decisioning
- Implement and scale data pipelines, features, and algorithms for production models
- Collaborate with engineering, credit, and product teams to define requirements for new products
- Present technical concepts and results to cross-functional audiences
You will be at the forefront of machine learning innovation in fintech, working on systems that enable consumers and partners to trust Affirm's decision-making processes.
Requirements:
- 2+ years of experience as a machine learning engineer, or PhD in a relevant field
- Proficiency in machine learning with experience in Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration (credit risk domain knowledge is a plus)
- Strong engineering skills in Python and SQL for data manipulation
- Experience with large-scale distributed systems such as Spark or Ray
- Experience with open-source ML tools: scikit-learn, pandas, NumPy, XGBoost, Kubeflow
- Demonstrated experience developing machine learning models at scale from inception to business impact
- Excellent written and oral communication skills with ability to drive cross-functional requirements
- Ability to present technical concepts in audience-appropriate ways
- Persistence, patience, and strong sense of responsibility
