Sagemaker DevOps Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Sagemaker DevOps Engineer in Spain.

Join an innovative and fast-paced technology environment where cloud infrastructure, automation, and machine learning come together to drive enterprise-scale transformation. In this role, you will play a key part in building and optimizing scalable MLOps and DevOps solutions focused on AWS SageMaker environments. You’ll collaborate with cross-functional engineering teams to automate machine learning workflows, streamline deployments, and improve operational efficiency across complex AI ecosystems. This opportunity is ideal for a technically strong engineer who enjoys solving infrastructure challenges and enabling data science teams to move faster and more reliably. Working remotely within an international environment, you’ll contribute to cutting-edge AI and cloud initiatives while leveraging modern DevOps best practices. The role offers strong ownership, exposure to advanced cloud technologies, and the ability to make a direct impact on enterprise AI delivery.

• Design, implement, and automate enterprise-grade AWS SageMaker environments and infrastructure solutions.
• Develop DevOps automation frameworks to support scalable machine learning operations and infrastructure management.
• Configure and maintain SageMaker lifecycle policies, ensuring optimized and reliable environments for ML teams.
• Build and manage CI/CD pipelines that enable users to deploy custom Docker images, kernels, and ML workloads efficiently.
• Create monitoring, alerting, and cost-control mechanisms for SageMaker services and enterprise ML projects.
• Support MLOps initiatives by automating model deployment processes and infrastructure promotion across environments.
• Collaborate with engineering, DevOps, and data teams to improve operational workflows and system reliability.
• Continuously enhance infrastructure scalability, performance, and security following DevOps and cloud best practices.

Requirements:

• 6+ years of experience in DevOps, Cloud Engineering, MLOps, or related technical roles.
• Expert-level knowledge of AWS services and strong proficiency in Python programming.
• Hands-on experience working with AWS SageMaker and machine learning infrastructure environments.
• Proven experience building enterprise-scale DevOps automation and cloud deployment solutions.
• Strong understanding of CI/CD concepts, infrastructure automation, and cloud-native architectures.
• Experience creating deployment pipelines using tools such as Jenkins is highly valued.
• Familiarity with Docker, containerized environments, and ML workflow automation is preferred.
• Experience with MLOps practices, model deployment automation, and monitoring solutions is a plus.
• Strong analytical and problem-solving abilities with a proactive and detail-oriented mindset.
• Excellent communication and collaboration skills in remote and cross-functional environments.

Benefits:

• Remote-first work environment across Europe
• Opportunity to work on cutting-edge AI, cloud, and MLOps projects
• Flexible employment options (Contractor or Full-time)
• Exposure to enterprise-scale cloud infrastructure initiatives
• Collaborative and innovation-driven engineering culture
• Career growth opportunities in advanced cloud and AI technologies
• Work alongside highly skilled international technical teams
• Inclusive and diverse workplace committed to equal opportunities
• Challenging and impactful projects with modern technology stacks