Closed listing
Machine Learning Engineer
- Toronto, ON, Canada
$70 to $85 CAD / hour · Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Pay
- $70 to $85 CAD / hour
- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
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.
More about this job
Responsibilities
Build and maintain production machine learning workloads, including Azure ML jobs, pipelines, model registries, endpoints, and CI/CD processes. Define and implement production monitoring and observability, and develop and evaluate time-series forecasts with appropriate backtesting and explainability methods.
Requirements
Requires 8+ years of ML, data, or software engineering experience, including substantial recent staff- or lead-level technical scope, along with strong Python, SQL, Snowflake, Azure ML, and CI/CD experience. Candidates should also have production monitoring and observability experience, time-series forecasting expertise, knowledge of explainability methods, and strong communication skills; planning platforms and retail or consumer goods experience are preferred.
Skills
- Python
- Machine Learning Engineering
- Data Engineering
- Software Engineering
- Azure Machine Learning
- SQL
- Snowflake
- Azure DevOps
- Machine Learning Monitoring
- Observability
- Explainability
- Time Series Forecasting
- Backtesting
- Stakeholder Communication
- Demand Planning
- Supply Chain
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Data & Analytics
- Software
- Retail
- Logistics
Keywords
- Python
- Machine Learning Engineering
- Data Engineering
- Software Engineering
- Azure Machine Learning
- Azure ML Jobs
- Azure ML Pipelines
- Model Registry
- Endpoints
- MLflow
- SQL
- Snowflake
- Performance Tuning
- Cost Tuning
- Azure DevOps
- CI/CD
- Monitoring
- Observability
- SHAP
- Permutation Importance
- Forecast Decomposition
- Time Series Forecasting
- Hierarchical Forecasts
- Intermittent Demand
- Backtesting
- o9 Solutions
- SAP IBP
- Kinaxis
- Blue Yonder
- Demand Planning