Closed listing
Senior AWS SageMaker / MLOps Engineer
- Toronto, ON, Canada
Contract
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Contract
- Closing date
- Experience
- 8+ years of overall IT experience.
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
8+ years of overall IT experience.
Strong hands-on experience with AWS SageMaker (training, deployment, monitoring, and inference).
Experience with SageMaker Pipelines, Model Registry, and Feature Store.
Strong expertise in MLOps concepts and ML lifecycle management.
Proficiency in Python programming.
Experience with AWS cloud services and cloud-native application development.
Experience with CI/CD tools such as Jenkins, GitHub Actions, or AWS CodePipeline.
More about this job
Responsibilities
Build and manage machine learning workflows using AWS SageMaker, including model training, deployment, monitoring, and inference. Support MLOps and machine learning lifecycle management using SageMaker Pipelines, Model Registry, Feature Store, and CI/CD tools.
Requirements
Requires 8 or more years of overall IT experience, hands-on AWS SageMaker experience, and strong knowledge of MLOps and machine learning lifecycle management. Proficiency in Python, AWS cloud services, cloud-native application development, and CI/CD tools such as Jenkins, GitHub Actions, or AWS CodePipeline is required.
Skills
- AWS SageMaker
- MLOps
- Python
- AWS Cloud Services
- SageMaker Pipelines
- SageMaker Model Registry
- SageMaker Feature Store
- CI/CD
- Jenkins
- GitHub Actions
- AWS CodePipeline
- Cloud-Native Application Development
- Model Training
- Model Deployment
- Model Monitoring
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Consulting
Keywords
- AWS SageMaker
- MLOps
- Python
- AWS Cloud Services
- SageMaker Pipelines
- Model Registry
- Feature Store
- CI/CD
- Jenkins
- GitHub Actions
- AWS CodePipeline
- Cloud-Native Application Development
- Model Training
- Model Deployment
- Model Monitoring
- Inference
- IT Services
- IT Consulting