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
