Location: Remote (Europe)

Experience: 6+ years

Employment Type: Contractor/Full-time

Overview

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 set up Sagemaker Unified Studio for enterprise
Implement Sagemaker Lifecycle configurations
Create CI/CD 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

Qualifications

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

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