Machine Learning Engineer

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 strong 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
• Strong hands-on experience with AWS cloud services
• Experience implementing MLOps pipelines and ML lifecycle management
• Strong 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