AWS Sagemaker / MLOPS Engineer

Toronto, ON

Hybrid: 2 days per week in-person at Toronto office preferred

Skills: Digital: Python | Digital: Azure Machine Learning (ML) | Digital: Terraform | AI & Gen AI - Products & Tools

Experience Required: 6–8 Years

Role Description:

We are looking for a highly experienced Senior AWS SageMaker / MLOps Engineer with 8+ years of overall IT experience and robust expertise in building, deploying, and operationalizing Machine Learning solutions on AWS.

The ideal candidate should have hands-on experience with AWS SageMaker, SageMaker Feature Store, MLOps frameworks, and Python development. The resource will be responsible for designing and implementing end-to-end ML pipelines, feature management strategies, model deployment automation, monitoring, and CI/CD integration for enterprise-scale machine learning platforms.

Top 3 Required Skills:
AWS SageMaker (Model Development, Training,



Deployment, Monitoring)
AWS SageMaker Feature Store and Feature Engineering
MLOps and Python Development

Top 3 Preferred Skills:
AWS Bedrock / Generative AI
Terraform / CloudFormation
Kubernetes and Docker

Experience Required:
8+ years of overall IT experience
Robust hands-on experience with AWS cloud services
Experience implementing MLOps pipelines and ML lifecycle management
Solid Python development skills
Hands-on experience with SageMaker Pipelines, Model Registry, and Feature Store
Experience with CI/CD tools and cloud-native development practices

Education Requirements:
Bachelor's degree in Computer Science, Engineering, Information Technology, or related field
AWS certifications preferred

📌 Aws Sagemaker / Mlops Engineer Toronto
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