Closed listing
AWS SageMaker / Machine Learning 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.
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
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
More about this job
Responsibilities
Develop, train, deploy, and monitor machine learning models using AWS SageMaker. Implement MLOps pipelines and manage the machine learning lifecycle, including feature engineering and use of SageMaker Pipelines, Model Registry, and Feature Store.
Requirements
Requires 8 or more years of overall IT experience, strong hands-on experience with AWS cloud services, and strong Python development skills. Candidates should have experience implementing MLOps pipelines and ML lifecycle management, with preferred experience in AWS Bedrock or generative AI, Terraform or CloudFormation, and Kubernetes and Docker.
Skills
- AWS SageMaker
- Machine Learning
- MLOps
- Python
- SageMaker Pipelines
- SageMaker Model Registry
- SageMaker Feature Store
- Feature Engineering
- CI/CD
- AWS Bedrock
- Generative AI
- Terraform
- CloudFormation
- Kubernetes
- Docker
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Engineering
Keywords
- AWS
- AWS SageMaker
- Machine Learning
- MLOps
- Python
- SageMaker Pipelines
- Model Registry
- Feature Store
- Feature Engineering
- ML Lifecycle Management
- Model Development
- Model Training
- Model Deployment
- Model Monitoring
- CI/CD
- Cloud-Native Development
- AWS Bedrock
- Generative AI
- Terraform
- CloudFormation
- Kubernetes
- Docker