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 solid 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

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📌 Full Stack Developer (Java / Angular / Python / AWS) - Tier1 Banking client (Toronto)
🏢 S.i. Systems
📍 Toronto