AWS ML Engineer
Role summary
This is a 6-month contract role for an AWS ML Engineer in Toronto, ON, with a hybrid work model. The primary focus is on designing, building, and deploying machine learning models and end-to-end ML workflows on AWS. Key responsibilities include developing data preprocessing, model training, inference, and monitoring pipelines, integrating ML models with applications, and optimizing performance, scalability, and cost. Collaboration with data scientists, data engineers, and DevOps teams in an Agile environment is expected. Preferred qualifications include hands-on experience with AWS ML and data services, understanding of ML lifecycle and MLOps, and familiarity with cloud deployment, automation, CI/CD, and version control.
Job Title: AWS ML Engineer
Location: Toronto, ON (Hybrid)
Duration: 6 months Contract with high possibility of extension
Job Description/Role
- AWS Machine Learning Engineer
Primary Skills
- Amazon SageMaker
- AWS Glue
- Amazon S3
- AWS Lambda
Key Responsibilities
- Design, build, and deploy machine learning models and pipelines on AWS
- Develop end-to-end ML workflows using SageMaker, Glue, S3, and Lambda
- Build data preprocessing, model training, inference, and monitoring pipelines
- Integrate ML models with applications using APIs and cloud services
- Optimize model performance, scalability, and cost on AWS infrastructure
- Collaborate with data scientists, data engineers, and DevOps teams in an Agile environment
Preferred Qualifications
- Hands-on experience with AWS ML and data services
- Strong understanding of ML lifecycle and MLOps practices
- Experience with cloud-based deployment and automation
- Familiarity with CI/CD pipelines and version control systems
