Summary
✨ AI‑Generated
Build production-grade machine learning systems for business forecasting. You will refactor models into tested reusable components, develop training and inference pipelines, automate deployment and rollback, create feature and data preparation workflows, and establish monitoring for data quality, drift, pipeline health, and forecast accuracy. The role bridges machine learning, data engineering, and platform operations.
Highlights
Production-focused ML engineering role centered on turning forecasting models into reliable, reusable systems. The work spans training and inference pipelines, deployment automation, monitoring, drift detection, model lineage, governance, and close collaboration with data science and planning teams.
Description
Day-to-Day
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.
Key Responsibilities
Refactor forecasting models into production-ready, tested, and reusable componentsEstablish engineering best practices, standards, and development workflowsDesign and maintain training, backtesting, and inference pipelines in Azure MLDevelop feature engineering and data preparation solutions in SnowflakeAutomate deployment, testing, model promotion, and rollback processes using Azure DevOpsSupport forecast integration with the o9 planning platformBuild monitoring for data quality, drift detection, pipeline health, and forecast accuracyImplement model lineage, traceability, and governance capabilitiesDevelop explainability solutions and forecasting insights for business usersCreate technical documentation and communicate solutions to both technical and business stakeholders
Required Skills & Experience
3+ years of ML Engineering, Data Engineering, or Software Engineering experienceStrong Python development and software engineering fundamentalsProduction experience with Azure ML (pipelines, compute, model registry, endpoints, MLflow)Strong SQL and Snowflake expertiseCI/CD experience using Azure DevOps or similar toolsExperience building ML monitoring and observability frameworksKnowledge of explainability techniques (SHAP, permutation importance, forecast decomposition)Time series forecasting experience, including backtesting and evaluationStrong communication and stakeholder management skills
Nice to Have Skills & Experience
Experience with o9 Solutions, SAP IBP, Kinaxis, or Blue YonderCPG, retail, or supply chain planning experienceDatabricks, Spark, dbt, Azure Data Factory, Power BIFeature stores, containerisation, and Infrastructure as Code (IaC)
Vacancy: This posting is for a currently vacant role, and the successful candidate will be hired into an existing open position.
Pay Rate: $60-70/hr
We may use artificial intelligence tools to assist with the screening, assessment, or selection of potential applicants for this position.
