Machine Learning Engineer, Underwriting

About this role

Bree, a rapidly growing Canadian fintech serving underserved consumers, seeks a Machine Learning Engineer to design and deploy production-grade ML systems for underwriting decisions. You'll build end-to-end pipelines, implement MLOps practices, and optimize models across the full lifecycle while collaborating with data engineering teams.

What you'll do

• Design and deploy end-to-end ML pipelines with focus on training, validation, and inference efficiency
• Implement MLOps best practices including CI/CD, model versioning, monitoring, and automated retraining
• Optimize models through feature engineering, hyperparameter tuning, and scalable inference techniques
• Deploy and manage models on cloud platforms (AWS, GCP, Azure) using Docker and Kubernetes
• Maintain model performance through continuous monitoring, bias detection, and explainability
• Collaborate with data engineers on high-performance data pipelines for training and inference

What they're looking for

• Python programming
• ML frameworks (Scikit-learn, LightGBM, PyTorch)
• MLOps tools (MLflow, Kubeflow, SageMaker)
• Data manipulation (Pandas, NumPy, SQL, NoSQL)
• Cloud-based ML deployment and infrastructure
• Real-time and batch inference pipeline development
• Machine learning algorithms (supervised and unsupervised)
• Docker and Kubernetes containerization

Benefits

• Competitive compensation for top performers
• Comprehensive health, dental, and vision coverage
• $1,500 annual learning and home-office stipend
• $1,000 annual wellness stipend
• 20 PTO days plus unlimited sick days and paid parental leave
• Monthly lunch stipend, commuter benefits, and quarterly team gatherings