Machine Learning Engineer, Underwriting

🕒 May 11

🇨🇦 Canada – Remote

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

👻 Ghost score 71%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Bree

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2021

💳 Fintech

👥 B2C

Fintech • B2C

Bree is a Canadian fintech company that provides small, short-term cash advances (up to CA$500) and an optional membership for consumers to avoid overdraft and predatory payday loans. It offers a tip-based, no-interest/no-fee cash advance model, a budgeting tool, and a weekly newsletter aimed at improving users' financial wellness, with clear repayment terms and mobile app access. Bree emphasizes community support and transparency in its mission to help Canadians manage short-term cash shortfalls.

📋 Description

• 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.

🎯 Requirements

• 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 annual learning & home-office stipend • $1,000 annual wellness stipend • Monthly Lunch Stipend • Commuter Benefits • Paid Parental leave • 20 annual PTO days + unlimited sick days • Quarterly Team Gatherings • In Office Amenities