Hybrid (Work Model)
2 days per week in-person at Toronto office preferred
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 Feature Store and Feature Engineering
MLOps and Python Development
Top 3 Preferred Skills
Kubernetes and Docker
Experience Required
8+ years of overall IT experience
Strong hands‑on experience with AWS cloud services
Experience implementing MLOps pipelines and ML lifecycle management
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