Machine Learning Engineer, Underwriting

Stack

Responsibilities

• ▹Design, develop and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation and inference
• ▹Implement MLOps best practices: CI/CD for ML models, model versioning, monitoring and retraining strategies
• ▹Optimize ML models using feature engineering, hyperparameter tuning and scalable inference techniques
• ▹Work with structured and unstructured data using Pandas, NumPy and SQL
• ▹Apply machine learning design patterns to build modular, reusable, production-ready models
• ▹Collaborate with data engineers on high-performance data pipelines for training and inference
• ▹Deploy and manage models on cloud platforms (AWS, GCP, Azure) with Docker and Kubernetes
• ▹Maintain model performance through continuous monitoring, bias detection and explainability techniques

Requirements

• ▹Proficiency in Python and familiarity with ML libraries such as Scikit-learn, LightGBM and PyTorch
• ▹Strong understanding of machine learning algorithms, including supervised and unsupervised learning
• ▹Experience with MLOps tools such as MLflow, Kubeflow or SageMaker
• ▹Hands-on experience with Pandas, NumPy and databases (SQL, NoSQL)
• ▹Knowledge of cloud-based ML deployment and infrastructure management
• ▹Ability to implement real-time and batch inference pipelines efficiently
• ▹Strong analytical and problem-solving skills to turn business needs into scalable ML solutions

Soft skills

What we offer

• ▹Top-of-the-market compensation for top performers
• ▹Comprehensive health, dental and vision benefits plan
• ▹$1,500 annual learning and home-office stipend
• ▹$1,000 annual wellness stipend
• ▹Monthly lunch stipend
• ▹Commuter benefits
• ▹Paid parental leave
• ▹20 annual PTO days and unlimited sick days
• ▹Quarterly team gatherings
• ▹In-office amenities

About the company

Bree is a consumer finance platform building faster, simpler and more affordable financial services for Canadians. With 800,000+ sign-ups, eight-figure annualized revenue and profitability, it is a Y Combinator Summer 2021 alumnus that raised a $2M seed round.