Machine Learning Engineer II, ROA, LTV ML

This is a fully remote position, open to applicants in Canada.

📋 Description

• Create machine learning models utilizing proprietary and third-party data to assess default probabilities and determine approval or denial decisions.

• Collaborate with platform and product engineering teams to establish systems for model training, decision-making, and monitoring.

• Investigate solutions and design prototypes for credit decision-making processes.

• Implement and enhance data pipelines, features, and algorithms for operational models.

• Work together with engineering, credit, and product teams to outline requirements for new products.

⛳️ Requirements

• A minimum of 2 years of experience as a machine learning engineer or a PhD in a related field.

• Expertise in machine learning techniques, including Generalized Linear Models, Gradient Boosting, Deep Learning, and Probabilistic Calibration.

• Strong programming skills in Python.

• Proficient in data manipulation, specifically using SQL.

• Experience with large-scale distributed systems such as Spark or Ray.

• Familiarity with tools like scikit-learn, pandas, NumPy, XGBoost, and Kubeflow.

• Proven experience in developing machine learning models at scale, from conception to delivering business impact.

• Exceptional written and verbal communication abilities.

• Capability to manage cross-functional requirements alongside product and engineering teams.

• Skill in presenting technical concepts and results effectively.

• Knowledge in credit risk is an added advantage.

🏝️ Benefits

• Monthly stipends for health, wellness, and technology expenses.

• Complete medical coverage for employees and their dependents at no cost.

• Dental and vision insurance for employees and their dependents.

• Flexible paid time off.

• Generous holiday schedules.

• Employee stock purchase plan (ESPP) allowing the purchase of Affirm stock at a discounted rate.

• Remote-first work flexibility.

• Comprehensive in-person onboarding experience.

• Inclusive interview process with accommodations available for candidates with disabilities.