AWS Sagemaker / MLOPS Engineer

Job Description

AWS Sagemaker / MLOPS Engineer

Toronto, ON

Hybrid: 2 days per week in-person at Toronto office preferred

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

Requirements
Java