Job Title: Senior AWS SageMaker / MLOps Engineer
Job Location:Toronto,ON-Hybrid (2 days per week in-person at Toronto office preferred)
Long Term Contract
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 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 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
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
Education Requirements:
Bachelor's degree in Computer Science, Engineering, Information Technology, or related field
AWS certifications preferred
