Senior AWS SageMaker / MLOps Engineer

Location: Toronto, ON

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

Role Description

We are looking for a highly experienced Senior AWS SageMaker / MLOps Engineer with 6+ years of overall IT experience and solid 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 Required Skills
AWS SageMaker – Model Development, Training, Deployment, and Monitoring
AWS SageMaker Feature Store and Feature Engineering
MLOps and Python Development

Top Preferred Skills




AWS Bedrock / Generative AI
Terraform / CloudFormation
Kubernetes and Docker

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

Skills
Python
AWS SageMaker
AWS SageMaker Feature Store
MLOps
AWS
AWS Bedrock / Generative AI
Terraform
CloudFormation
Kubernetes
Docker
CI/CD
Azure Machine Learning (ML)

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

📌 Machine Learning Engineer Ontario (Canada)
🏢 IMCS Group
📍 Canada