Affirm is hiring a remote ML Engineer II ROA + LTV ML!
Affirm is hiring a Machine Learning Engineer II to join the team behind its risk-oriented underwriting models, specifically the return on assets (ROA) and lifetime value (LTV) modeling work. The role centres on building production-grade models that estimate the probability of default and translate those predictions into approve-or-decline credit decisions. This is a remote position open to candidates living in Alberta, British Columbia, Manitoba, New Brunswick, Newfoundland and Labrador, Nova Scotia, Ontario, Prince Edward Island, or Saskatchewan, with an annual base pay range of CAD $133,000 to $183,000 plus equity, health and wellness stipends, and other benefits. The engineer works closely with platform, product, and credit teams, so the job blends hands-on modeling with cross-functional collaboration and production systems work.
Key responsibilities
- Develop models that predict default likelihood and drive approval or decline decisions, using Affirm's proprietary data alongside third-party sources.
- Collaborate with platform and product engineers to build and maintain systems for model training, decisioning, and ongoing monitoring.
- Prototype and research new approaches that could shape the future of credit decisioning.
- Build and scale data pipelines, features, and algorithms that feed production models.
- Work with engineering, credit, and product stakeholders to define requirements for new products and translate them into modeling work.
Key requirements
- At least two years of experience as a machine learning engineer, or a PhD in a relevant discipline.
- Solid grounding in machine learning methods such as generalized linear models, gradient boosting, deep learning, and probabilistic calibration; credit risk domain knowledge is an asset.
- Strong Python engineering ability and comfort with SQL for data manipulation.
- Experience with large-scale distributed systems such as Spark or Ray.
- Familiarity with open-source tooling including scikit-learn, pandas, NumPy, XGBoost, and Kubeflow.
- A track record of taking models from initial development through to measurable business impact at scale.
- Clear written and verbal communication, including the ability to drive cross-functional requirements and present technical results to varied audiences.
- Persistence, patience, and a strong sense of responsibility for the decisions consumers and partners rely on.
- Seniority: Mid-level (Engineer II)
- Work mode: Remote (Canada; specific provinces only)
- Salary: CAD $133,000 - $183,000 per year
- Key skills: Python, SQL, Spark, Ray, scikit-learn, pandas, NumPy, XGBoost, Kubeflow, Generalized Linear Models, Gradient Boosting, Deep Learning, Probabilistic Calibration, Credit Risk Modeling
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