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
Robust 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

📌 Full Stack Developer Java / Angular / Python / Aws T Banking Client Toronto (Canada)
🏢 S.i. Systems
📍 Canada