MLOps Engineer: Scale AI in the Cloud

Springer Nature Group; Groningen; On-site; EUR 70,000 - 110,000; Full time

Job summary

Springer Nature Group is seeking a skilled MLOps Engineer to design, deploy, and operate scalable AI/ML platforms in cloud environments. You will bridge ML development and production operations, ensuring reliable, secure, and scalable AI systems aligned with business needs.

You will mentor teammates, contribute to DevOps best practices, and stay ahead on emerging AI technologies while collaborating across functions to deliver high-impact AI-enabled capabilities.

Qualifications

• A degree in Software Engineering, Computer Science, Artificial Intelligence, or a related technical field.
• Strong experience developing software solutions using Python and modern engineering practices.
• Experience with GitHub, Docker, and machine learning frameworks such as PyTorch or TensorFlow.
• Hands-on experience working with cloud platforms such as Azure, AWS, or GCP.
• Experience building APIs and services using FastAPI or similar frameworks.
• Knowledge of CI/CD pipelines, automated testing frameworks, and GitHub Actions.
• Experience implementing observability, monitoring, and tracing solutions for AI and ML applications, including Langfuse or equivalent platforms.
• Understanding of machine learning lifecycle management, deployment strategies, and production monitoring.
• Experience deploying and monitoring AI agents and LLM-based applications is considered an advantage.
• Having a good command of English is important; collaboration is important in our day to day work, so being able to communicate your ideas and understand others’ is key.

Responsibilities

• Design, build, and maintain scalable MLOps platforms, frameworks, and deployment pipelines that support the reliable delivery of machine learning and generative AI solutions.
• Develop and integrate cloud-native services, automation workflows, and CI/CD practices to improve operational efficiency, system reliability, and deployment velocity.
• Implement monitoring, observability, tracing, and performance management capabilities to proactively identify issues and optimize production systems.
• Drive process optimization initiatives that improve model lifecycle management, operational resilience, governance, and overall team effectiveness.
• Contribute to data security, compliance, and governance standards by ensuring appropriate controls, monitoring, and responsible management of AI and data assets.
• Support knowledge sharing, technical storytelling, and documentation to increase transparency, adoption, and understanding of AI capabilities across the organization.
• Mentor and support junior engineers, helping develop MLOps and AI engineering capabilities across the team.
• Stay current with emerging technologies, AI engineering practices, and industry trends, identifying opportunities to enhance our platforms and delivery approaches.

Skills

Python

CI/CD

Observability

English communication

Education

Bachelor's degree in Software Engineering/CS/AI

Tools

GitHub

Docker

FastAPI

Langfuse

PyTorch

TensorFlow

GitHub Actions

Job description

Springer Nature Group is seeking a skilled MLOps Engineer to design, deploy, and operate scalable AI/ML platforms in cloud environments. You will bridge ML development and production operations, ensuring reliable, secure, and scalable AI systems aligned with business needs.

You will mentor teammates, contribute to DevOps best practices, and stay ahead on emerging AI technologies while collaborating across functions to deliver high-impact AI-enabled capabilities.