2 months ago
Toronto, CanadaIntern
Responsibilities
- Design, train, and deploy scalable machine learning models for credit risk assessment, fraud detection, and personalized financial recommendations.
- Architect ML pipelines integrated with backend systems to process high-throughput data streams and support low-latency inference.
- Use AI tools to automate experimentation, hyperparameter tuning, and test-driven ML development.
- Support the full ML lifecycle, including feature engineering, model evaluation, A/B testing, drift monitoring, and scaling.
- Experiment with deep learning and reinforcement learning techniques while maintaining compliance with financial regulations.
Requirements
- Professional experience building and deploying production ML systems and handling imbalanced datasets in high-stakes domains such as finance or e-commerce.
- Strong understanding of traditional ML systems and modern deep learning and reinforcement learning architectures, with experience applying them to real-world problems.
- Architectural thinking and experience scaling ML systems while maintaining accuracy, fairness, and explainability.
- Strong collaboration and communication skills, including the ability to explain complex ML concepts to non-technical stakeholders.
- Competitive ML experience, such as strong Kaggle or NeurIPS challenge rankings or open-source contributions, is preferred.
Benefits
- 8-month co-op term available.
- $250 monthly lunch stipend and a bi-annual company retreat.
- Mentorship programs and career training sessions.
- Strong full-time conversion opportunities for high performers.
- Opportunity to work in a high-ownership role with direct production impact.
Tech Stack
LightGBMPyTorch
Categories
