- Canada
- Hybrid
- Full-time · Senior
- 3+ years
Own the end-to-end ML lifecycle, from dataset creation and foundational research to building and deploying production-grade models.
Responsibilities
- Research, design, and implement novel machine learning solutions using modern architectures to tackle complex business problems.
- Build and manage efficient pipelines for rapid experimentation and hypothesis testing.
- Methodically design, execute, and track all experiments, including hyperparameter searches, architecture changes, and data variations, using tools like MLflow or Weights & Biases.
- Deploy models into production environments using CI/CD practices and model serving frameworks.
- Implement and maintain robust monitoring systems to track model performance, detect drift, and ensure reliability and scalability.
Requirements
- Bachelor's degree in Computer Science, AI, Data Science, or a related technical field
- Master's degree in Computer Science, AI, Data Science, or a related technical field
- Nice to have: Transformers
- Nice to have: Mixtures of Experts (MoE)
- Nice to have: MLOps lifecycle