Hybrid Machine Learning Engineer for Advanced Models
mississauga, peel region, Canada • Posted May 31, 2026
Job Type:
Full-time
Location:
mississauga, peel region
Posted:
May 31, 2026
Category:
Engineering
Application Deadline:
July 10, 2026
Role Description
Transform utility operations as a skilled Machine Learning Engineer. Focus on the deployment of innovative machine learning and deep learning models designed to make data-driven decisions within fast-paced environments while utilizing hybrid work flexibility.
In this role, you will oversee the entire lifecycle of machine learning systems, ensuring top-tier model performance and operational efficacy. The position emphasizes scalable architecture, practical MLOps practices, and leveraging time-series and geospatial data to drive insights crucial to utility management.
Key Responsibilities:
• Create and support machine learning systems for real-time operations
• Oversee rigorous model evaluation and benchmarking strategies
• Maintain end-to-end MLOps pipelines with reliability
• Address challenges of large-scale and incomplete datasets
• Collaborate across teams to implement effective solutions
Requirements:
• Bachelor’s degree in a related field or equivalent
In this role, you will oversee the entire lifecycle of machine learning systems, ensuring top-tier model performance and operational efficacy. The position emphasizes scalable architecture, practical MLOps practices, and leveraging time-series and geospatial data to drive insights crucial to utility management.
Key Responsibilities:
• Create and support machine learning systems for real-time operations
• Oversee rigorous model evaluation and benchmarking strategies
• Maintain end-to-end MLOps pipelines with reliability
• Address challenges of large-scale and incomplete datasets
• Collaborate across teams to implement effective solutions
Requirements:
• Bachelor’s degree in a related field or equivalent
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