Sagemaker DevOps Engineer

Jobgether • Germany

Remote

This Job is No Longer Active This position is no longer accepting applications

AI Summary

We are seeking an experienced Sagemaker DevOps Engineer to design, automate, and maintain cloud-based MLOps solutions. The ideal candidate will have expertise in AWS services, Python development, and Amazon SageMaker. The role involves collaborating with cross-functional engineering teams to deliver reliable, secure, and automated cloud environments.

Key Highlights

Design, build, and automate enterprise-grade AWS SageMaker environments

Develop and implement DevOps automation for SageMaker Unified Studio and related cloud infrastructure

Collaborate with engineering and platform teams to continuously improve cloud architecture, deployment processes, and operational best practices

Key Responsibilities

Design, build, and automate enterprise-grade AWS SageMaker environments to support scalable machine learning initiatives

Develop and implement DevOps automation for SageMaker Unified Studio and related cloud infrastructure

Configure and maintain SageMaker lifecycle configurations to improve development consistency and operational efficiency

Build and optimize CI/CD pipelines that enable users to deploy custom Docker images, kernels, and machine learning workloads

Develop monitoring, alerting, and cost-control mechanisms to ensure platform reliability, service availability, and efficient resource utilization

Implement MLOps automation for model deployment and infrastructure promotion across multiple environments

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Technical Skills Required

Amazon Web Services Python Amazon SageMaker

Benefits & Perks

Fully remote position within Europe

Flexible engagement as either a contractor or full-time employee

Opportunity to work on cutting-edge AI, cloud, and machine learning projects

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Nice to Have

Experience building Jenkins pipelines

Experience implementing MLOps workflows and automated model deployment processes

Job Description

This is an excellent opportunity for an experienced DevOps professional to help build and optimize enterprise-scale machine learning infrastructure in a fully remote environment. In this role, you will design, automate, and maintain cloud-based MLOps solutions that enable seamless model development, deployment, and operations. Working at the intersection of DevOps and machine learning, you will create scalable platforms, improve development workflows, and enhance operational efficiency across AI initiatives. You will collaborate with cross-functional engineering teams to deliver reliable, secure, and automated cloud environments. This position offers the chance to work with modern AWS technologies while contributing to high-impact, enterprise-level projects. It is ideal for professionals who enjoy solving complex infrastructure challenges and driving automation at scale.

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