Machine Learning Engineer II (ROA + LTV ML)

Role overview Develop and operate machine learning models that support credit approval decisions, with a focus on predicting default risk and meeting business goals. The work spans model research, production systems, and collaboration with product, credit, and engineering teams.

Responsibilities - Build models using proprietary and third-party data to estimate default risk and inform approval decisions. - Work with platform and product engineers on model training, decision systems, and monitoring. - Research approaches and prototype improvements to credit decisioning. - Build and scale data pipelines, features, and algorithms used by production models. - Partner with engineering, credit, and product colleagues to define requirements for new products.

Requirements - At least two years of machine learning engineering experience, or a PhD in a relevant field. - Practical machine learning knowledge, including methods such as generalized linear models, gradient boosting, deep learning, or probabilistic calibration. - Strong Python and SQL skills, plus experience with distributed systems such as Spark or Ray. - Experience with machine learning tools such as scikit-learn, pandas, NumPy, XGBoost, or Kubeflow. - Experience taking machine learning models from early development through scaled deployment and business impact. - Clear communication skills, including the ability to explain technical results and coordinate requirements across teams.

Nice to have - Familiarity with credit risk. - Persistence and a strong sense of responsibility when building systems used for consequential decisions.

Benefits and work setup - Remote role for candidates residing in specified Canadian provinces and territories. - Listed annual base salary range: CAD $133,000–$183,000. Total compensation may include equity, health coverage, and monthly spending stipends. - Benefits include employer-paid medical, dental, and vision premiums for employees and dependents, flexible time off, holiday calendars, and a discounted employee stock purchase plan.