Machine Learning Engineering, Intern at bree. About the role In this internship position, you will engage with machine learning systems tailored for a consumer finance platform. Your primary responsibility will be to assist in the development and deployment of models that enhance essential financial services for a diverse user base. The role emphasizes leveraging AI technologies to rapidly iterate on models, ensuring the delivery of impactful solutions that meet user needs.

Key facts

Location: Toronto

Engagement: Internship, with a preference for an 8-month co-op term

Compensation: $50-$65/hour, contingent on experience and performance during the interview

Team: Internship & Co-ops

What you'll do

- Design, train, and implement machine learning models specifically for financial applications, including credit risk assessment, fraud detection, and personalized user recommendations, utilizing frameworks such as PyTorch and LightGBM.
- Develop machine learning pipelines that seamlessly integrate with backend systems, enabling the processing of large data volumes and facilitating real-time decision-making.
- Employ AI tools to automate experimental processes, optimize hyperparameters, and create machine learning models grounded in a test-driven methodology.
- Participate in the full machine learning lifecycle, which encompasses feature engineering, model evaluation, A/B testing, drift monitoring, and scaling solutions to manage user growth while adhering to financial regulations.




- Investigate and apply advanced techniques in deep learning and reinforcement learning to drive innovation within the consumer finance sector.
- Collaborate with cross-functional teams to ensure alignment between machine learning initiatives and business objectives.
- Analyze and interpret complex datasets to derive actionable insights that inform model development and optimization.
- Document processes and findings to contribute to knowledge sharing within the team and the broader organization.

Requirements

- Proven experience in building and deploying machine learning systems in production environments, particularly with imbalanced datasets in critical sectors such as finance or e-commerce.
- A solid grasp of both traditional machine learning frameworks and contemporary deep learning/reinforcement learning architectures, complemented by hands‑on application experience.
- Solid architectural thinking skills to navigate ambiguous, data‑driven challenges in dynamic settings, including the ability to scale machine learning systems during periods of rapid growth while ensuring accuracy, fairness, and interpretability.
- Exceptional collaboration and communication abilities, particularly in articulating complex machine learning concepts to non-technical stakeholders.




- A proactive approach to problem-solving and a willingness to learn and adapt in a fast-paced environment.
- A background in statistics or mathematics is advantageous for understanding model performance metrics.

Nice to have

- Competitive experience in machine learning, such as notable rankings in Kaggle competitions or contributions to open-source projects in the field.
- Familiarity with cloud computing platforms (e.g., AWS, Azure) for deploying machine learning models.
- Experience with data visualization tools to present findings effectively.

Skills & tools

- Proficiency in PyTorch for building deep learning models.
- Experience with LightGBM for efficient gradient boosting.
- Familiarity with data manipulation libraries such as Pandas and NumPy.
- Knowledge of version control systems, particularly Git, for collaborative development.

Practical notes

- Bree is willing to consider matching competing offers to attract top talent.
- Interns will receive a monthly lunch stipend of $250, along with opportunities for bi-annual company retreats that foster team bonding and professional development.
- High-performing interns have a strong chance of transitioning into full-time positions upon successful completion of their internship, providing a pathway to a rewarding career in machine learning and data science.

This internship at bree offers a unique opportunity to work at the intersection of technology and finance, contributing to innovative solutions that impact users' financial experiences.

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📌 Machine Learning Engineering, Intern (Toronto)
🏢 Bree
📍 Toronto