Insight Global is looking for a Machine Learning Engineer to put into production forecasting models and build the monitoring, observability, and explain capabilities needed for trusted business forecasting.

The role partners closely with data scientists, demand planners, and platform teams to deliver scalable and reliable forecasting solutions.

Refactor forecasting models into production-ready, tested, and reusable components

Design and maintain training, backtesting, and inference pipelines in Azure ML

Develop feature engineering and data preparation solutions in Snowflake

Automate deployment, testing, model promotion, and rollback processes using Azure DevOps

Support forecast integration with the o9 planning platform

Build monitoring for data quality, drift detection, pipeline health, and forecast accuracy





Create technical documentation and communicate solutions to both technical and business stakeholders

3+ years of ML Engineering, Data Engineering, or Software Engineering experience

Solid Python development and software engineering fundamentals

Azure ML (pipelines, compute, model registry, endpoints, MLflow)

SQL Azure DevOps Experience building ML monitoring and observability frameworks

Knowledge of explainability techniques (SHAP, permutation importance, forecast decomposition)

o9 Solutions , SAP IBP, Kinaxis, or Blue Yonder

CPG, retail, or supply chain planning experience

We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position. #

📌 Machine Learning Engineer (Python / Data Science) (Toronto)
🏢 Insight Global
📍 Toronto