Machine Learning Engineer, Underwriting

The role

You will design, develop, and deploy end-to-end machine learning pipelines. You will implement MLOps best practices and optimize ML models using various techniques.

What you will do

• Design, develop, and deploy end-to-end machine learning pipelines
• Implement MLOps best practices including CI/CD, versioning, monitoring, and retraining
• Optimize ML models using feature engineering, hyperparameter tuning, and scalable inference
• Work with structured and unstructured data using Pandas, NumPy, and SQL
• Apply machine learning design patterns to build production-ready models
• Collaborate with data engineers to develop high-performance data pipelines
• Deploy and manage models on cloud platforms using Docker and Kubernetes
• Maintain model performance through monitoring, bias detection, and explainability

Required qualifications

• Proficiency in Python
• Familiarity with ML libraries like Scikit-learn, LightGBM, and PyTorch
• Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker
• Hands-on experience with data manipulation libraries (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

Benefits

• Top of the market compensation for top performers
• Comprehensive health, dental, and vision benefits plan
• $1,500 one-time setup + $500/year annual learning & home-office stipend
• $1,500 annual wellness stipend
• Free lunch provided in office daily
• Commuter Benefits
• Paid Parental leave
• 20 annual PTO days + unlimited sick days
• Quarterly Team Gatherings
• In Office Amenities

About the company

Bree is a consumer finance platform building financial services for Canadians. They were part of Y Combinator (Summer 2021).