Rocket Innovation Studio (RIS) is looking to improve the mortgage process and deliver an excellent client experience for Canadians by leveraging machine learning and data science
Requirements
- Strong Python (pandas, NumPy, scikit‑learn); solid SQL
- Git proficiency; comfort with code reviews and branching (GitHub/GitLab)
- Knowledge of ML lifecycle: data prep, training, validation, packaging, inference
- Linux/CLI fluency; scripting mindset and attention to reproducibility
- Fundamentals in testing (unit/integration) and debugging
- Exposure to AWS (S3, IAM, Lambda/ECS/EKS, SageMaker) or equivalent cloud
- ML Ops tooling: MLflow, feature stores, model registry, experiment tracking
Responsibilities
- Set up and test connections between SageMaker, MLflow, and the feature store
- Select an internal or public dataset for a classification/regression task
- Engineer features, register them in the feature store, and document schema/lineage
- Train and version a baseline ML model (e.g., XGBoost or sklearn) in SageMaker
- Log metrics, artifacts, and parameters in MLflow; register the model for deployment
- Deploy the model to a dev endpoint and create a basic monitoring dashboard (Dynatrace)
- Write clear documentation so future interns/new hires can replicate the workflow
Other
- Currently pursuing MS/PhD in CS, DS, EE, or related field
- Clear written communication; concise documentation
- Minimum Qualifications: strong academic background and relevant skills
- Preferred Qualifications: practical experience from coursework/projects/internships open‑sourced or well‑documented
- Eligibility for company benefits and perks
