Build production machine learning systems with AWS SageMaker, Python, and SQL in a flexible hybrid engineering role. Work two days weekly in Toronto. As a Senior MLOps and Cloud Engineer, you will deploy models, operate pipelines, and manage AWS infrastructure. You will configure batch and real-time inference, automate data transformations, and collaborate directly with business teams. Jira supports project execution and delivery ownership. Key Responsibilities:

Deploy and operationalize machine learning models on AWS Manage SageMaker workflows and inference endpoints Automate Python and SQL data pipelines Optimize CI/CD, containers, and cloud infrastructure Monitor production metrics and initiate retraining Requirements:

Seven years of technical experience targeted; four to five-plus considered Bachelor's degree or equivalent practical experience Solid Python and SQL proficiency Hands-on AWS SageMaker deployment experience Git, CI/CD, Docker, ECS, or EKS experience Apply AWS, SageMaker, Python, and SQL expertise to own reliable machine learning delivery from pipelines through production.

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📌 Senior AWS MLOps Engineer (Winnipeg)
🏢 Randstad Digital
📍 Winnipeg