Posted last month
AWS Sagemaker / MLOPS Engineer
@ Astra North Infoteck Inc.
Toronto, Ontario
Overview
Astra North Infoteck Inc. is hiring a contract Senior AWS SageMaker / MLOps Engineer in Toronto, ON, on a hybrid arrangement with two days a week in-person preferred. The role builds, deploys and operationalizes machine learning solutions on AWS, requiring 6 to 8 years of experience.
Responsibilities:
- Design and implement end-to-end ML pipelines
- Manage feature engineering with SageMaker Feature Store
- Automate model deployment and monitoring
- Integrate CI/CD for ML platforms
Requirements summary:
- 8+ years of overall IT experience
- Hands-on AWS SageMaker experience
- Strong Python and MLOps skills
- Bachelor's degree in a related field
Tools & skills
Source and dates
Source type not verified · zoho
- Employer posting date
- 2026-10-07
- First seen by our source
- 2026-10-11
- Source record updated
- 2026-10-11
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Data & analytics |
| Experience | 6+ years |
| Travel | air: none · ground: none |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required) |
| Fields of study | Computer Science, Engineering, Information Technology |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Astra North Infoteck Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 426 |
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
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