Machine Learning Engineer

Our client is a multi-brand retailer based in Montreal, Canada specializing in the sale of designer fashion and high-end streetwear. It was founded as an e-commerce platform in 2003.

Requirements:

• Solid experience with SageMaker Studio and all features it provides (Sagemaker Pipelines)
• Ability to create and adjust SageMaker pipelines for the end-to-end ML development cycle
• Experience with deploying model inference with Sagemaker endpoints and other serverless computing (such as Lambda)
• Experience with transferring projects from on-premise to SageMaker
• Ability to understand machine learning development and deployment processes
• Good knowledge of how to deploy model inference with CodePipeline

Responsibilities:

• Collaborate with client to understand their current machine learning development environment setup
• Provide guidance and best practices to client on how to effectively and securely setup SageMaker Studio domain
• Design, implement and manage AWS infrastructure for the ML environment, including VPCs, subnets, security groups, and other AWS resources
• Work with clients to configure AWS IAM roles, policies, and permissions to ensure secure access to AWS resources and data
• Identify opportunities for optimization and cost reduction in the AWS infrastructure and SageMaker Studio environments
• Create reusable project templates to create the infrastructure for MLOps solution for CI/CD of ML models
• Conduct workshops for client on how to use SageMaker Studio features effectively