# Machine Learning Engineer at Bree Machine Learning Engineer at Bree in Canada. Hybrid, full-time, paying $180k–$250k. Posted April 1, 2026. - Company: Bree - Location: Canada - Workplace: Hybrid - Job type: Full-time - Pay: $180k–$250k - Posted: 2026-04-01 - Apply: https://jobs.ashbyhq.com/bree/d5fe10d5-d3fa-4a89-a93f-3685570a7106/application - Source: https://jobmagic.ai/jobs/machine-learning-engineer-bree-jk4fxk ## Description ### **About Bree** Bree is a consumer finance platform building faster, simpler, and more affordable financial services for Canadians who often live paycheck to paycheck. We operate in a massive market that’s historically been underserved by traditional financial institutions, and we’re building products that help customers access short-term credit with a transparent, user-first experience. To date, 800,000+ Canadians have signed up for Bree—and we believe we’re still early. We’re at an exciting intersection of product-market fit, rapid growth, and a clear path to becoming one of the most important fintech companies in Canada. We were part of Y Combinator (Summer 2021) and raised a $2M seed round shortly after.   ### **About the Role** We’re looking for aMachine Learning Engineer to build and scale high-impact, world-class ML systems. You’re passionate about deploying AI solutions, optimizing performance, and driving measurable results. Your work will power critical decisions and shape the future of our technology.   ### **What You'll Do** - Design, develop, and deploy end-to-end machine learning pipelines, ensuring efficiency in training, validation, and inference. - Implement MLOps best practices, including 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, leveraging Pandas, NumPy, and SQL for efficient data manipulation. - Apply machine learning design patterns to build modular, reusable, and production-ready models. - Collaborate with data engineers to develop high-performance data pipelines for training and inference. - Deploy and manage models on cloud platforms (AWS, GCP, Azure) with containerization and orchestration tools like Docker and Kubernetes. - Maintain model performance by implementing continuous monitoring, bias detection, and explainability techniques.   ### **What You'll Need** - Proficiency in Python and 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 for tracking experiments and automating workflows. - 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 to translate business needs into scalable ML solutions. - Eagerness to work in a fast-paced environment and continuously refine ML processes for efficiency and accuracy.   ### **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 + $250/Month Stipend For Your WFH Days ❄️ Fully Remote In The Winter 🚗 $150/Month Commuter Benefits 🚼 Parental Leave 🏝 20 Annual PTO Days + Unlimited Sick Days 🚀 Annual Company Retreat ☕ In-Office Amenities