DevOps Engineer

The Sagemaker DevOps Engineer acts as the bridge between standard infrastructure and the specialized needs of Machine Learning (ML). Your primary goal is to take the “manual” out of ML. You will be responsible for architecting the environment (SageMaker), ensuring it scales across an enterprise, and automating the journey a model takes from a developer’s laptop to a production environment. Responsibilities

• Build DevOps automations to setup Sagemaker Unified Studio for enterprise
• Implement Sagemaker Lifecycle configurations
• Create CICD pipelines for end-users to deploy custom Docker images & Kernels in Sagemaker
• Build alert & monitoring capabilities for Sagemaker projects to control costs and service quotas
• MLOps automations for model and infrastructure deployments to higher environments

• From 6+ years of experience in a relevant role
• Expert level in AWS and Python
• Working knowledge with Sagemaker
• Experience building DevOps automations for enterprise
• Preferred to have experience building Jenkins pipelines
• Preferred to have experience with MLOps automations