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    • Strong understanding of machine learning algorithms, including supervised and unsupervised learning techniques.
    • 20 Annual PTO Days + Unlimited Sick Days.
    • View all Bree jobs - Toronto jobs
    • Salary Search: Machine Learning Engineer salaries in Toronto, ON
    • Ship quickly while learning, and adjust course as the industry shifts.
    • Engineering, Product, Design, and MarketingEngineering.
    • 401(k) and RRSP matching.
    • Hands-on experience with statistics and machine learning.
    • We’re looking for Machine Learning Engineers who are passionate about building cutting-edge systems…
    • You'll work where machine learning, biomechanics, physiology, and computer vision meet.
    • We take into consideration an individual’s background, experience, and…
  • View similar jobs with this employer
    • Strong programming skills in Python for implementing machine learning models, data pipelines, and training workflows.
    • What Makes You Stand out.
  • View similar jobs with this employer
    • Experience with classical ML or deep learning model development.
    • Solid machine learning/data science background: you understand experimental design, data splits…
    • You will work extensively with AI coding and design agents, take ownership of product quality, and help shape how we develop and deliver software using AI.
    • Designing and deploying end-to-end AI and machine learning solutions for remote monitoring, predictive insights, anomaly detection, and intelligent alerting.
    • Experience: 7+ years of industry experience in software engineering with a strong focus on applied machine learning, deep learning, or NLP.
    • Proficiency in Python along with experience with machine learning libraries and frameworks (e.g. scikit-learn, XGBoost,...).
    • 5+ years of experience in machine learning engineering or applied data science.
    • Machine learning engineering or applied data science: 5 years (required).
    • This Senior Data Engineer role offers the opportunity to build and lead a modern data engineering practice within a growing fintech organization.
    • Just a machine that makes money and wants to go faster.
    • You have operated event-driven or streaming systems at scale, and when something is one machine with no…
    • We're not bolting AI onto old workflows — we're rebuilding them from the ground up.
    • Own and evolve our image processing pipeline — CAD feature detection,…
    • *Computer vision and deep learning.
    • Own the technical direction for computer vision and neural network models that extract, check and compare information from…
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Job Post Details

Machine Learning Engineer
Bree
Toronto, ON
•
Hybrid work
$180,000–$250,000 a year
Full-time
Apply on company site

Job details

$180,000–$250,000 a year
Paid time off, Vision care, Dental care, Commuter benefits
Full-time
Hybrid work in Toronto, ON

Full job 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 a Machine 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

Compensation Range: CA$180K - CA$250K

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