MLOps Engineer

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