Pay: 70-85
Contract Duration: 12 MO
Work Arrangement: Hybrid Toronto
We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position.
Vacancy: This posting is for a currently vacant role, and the successful candidate will be hired into an existing open position.
Required qualifications
- 8+ years in ML engineering, data engineering, or software engineering, with substantial recent time at a staff/lead level of technical scope.
- Strong Python and software engineering fundamentals - testing, packaging, code review, refactoring legacy or exploratory code without breaking behavior.
- Production experience with Azure ML: jobs, pipelines, compute, model registry, endpoints, MLflow tracking.
- Strong SQL and Snowflake experience, including performance and cost tuning on large tables.
- CI/CD experience with Azure DevOps (or equivalent) for ML workloads.
- Demonstrated experience building ML monitoring and observability in production - not just standing up a dashboard, but defining what to measure and what to do when it moves.
- Working knowledge of explainability methods (e.g. SHAP, permutation importance, forecast decomposition) and the judgment to know their limits.
- Time series forecasting experience: hierarchical forecasts, intermittent demand, proper backtesting and evaluation design.
- Clear written and verbal communication with non-technical stakeholders.
Nice to have
- Direct experience with o9 Solutions, or comparable planning platforms (SAP IBP, Kinaxis, Blue Yonder).
- CPG, retail, or consumer goods demand planning and supply chain context.
- Databricks/Spark, dbt, Azure Data Factory, Power BI.
- Feature store, containerization, or infrastructure-as-code experience.
