MLOps Engineer

1100 Springer Nature B.V.; Groningen; On-site; EUR 70,000 - 100,000; Full time

Job summary

Springer Nature is seeking a MLOps Engineer to join the SN AI Lab in Groningen, the Netherlands. You will design, deploy, and scale AI solutions in cloud environments, bridging ML development and production operations to ensure reliable, secure systems.

You will build scalable pipelines, implement CI/CD, observability, and governance, and collaborate with engineers across functions. Proficiency in Python, Docker, and cloud platforms is essential, with a passion for responsible AI.

Qualifications

• A degree in Software Engineering, Computer Science, or a related field.
• Strong experience with Python and modern engineering practices.
• Hands-on cloud experience across Azure, AWS, or GCP, and API development using FastAPI.
• Knowledge of CI/CD, testing, and GitHub Actions.
• Experience with observability and production monitoring for AI systems.

Responsibilities

• Design, build, and maintain scalable MLOps platforms and deployment pipelines.
• Develop and integrate cloud-native services and CI/CD workflows.
• Implement monitoring, observability, tracing, and performance management.
• Improve model lifecycle management and governance.
• Ensure data security, compliance, and responsible AI practices.
• Mentor juniors and share knowledge across the team.

Skills

Python

GitHub

CI/CD

APIs

Education

Bachelor's degree in Software Engineering or Computer Science

Tools

Docker

FastAPI

PyTorch

TensorFlow

Azure

AWS

GCP

Job description

Job Title: MLOPs Engineer Location(s): Groningen, the Netherlands

About Springer Nature

Springer Nature opens the doors to discovery for researchers, educators, clinicians and other professionals. Every day, around the globe, our imprints, books, journals, platforms and technology solutions reach millions of people. For over 175 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood and used by our communities – enabling them to improve outcomes, make progress, and benefit the generations that follow.

About the Us

At Springer Nature AI Lab (SNAIL), we are shaping the future of scientific publishing through responsible, human-centered AI. Our team is at the forefront of integrating advanced AI technologies to optimize processes and enhance the user experience for researchers and academics worldwide. We value a collaborative work environment where ideas flourish and innovation is encouraged. With our curiosity-driven, impact-first culture, we focus on delivering AI innovation at scale, always with integrity and in close collaboration across functions. Our commitment to long-term growth ensures that our people are nurtured and developed to reach their full potential.

About the Role

As a MLOps Engineer within the SN AI Lab, you will join a team of engineers designing, deploying, and scaling innovative AI solutions in cloud environments. You will play a critical role in bridging machine learning development and production operations, ensuring AI systems are reliable, secure, scalable, and aligned with business needs. Working in a fast-paced and collaborative environment, you will contribute to the end-to-end delivery of AI products, driving engineering excellence, operational efficiency, and responsible AI practices across the organization.

Role 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.

About You

• 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 machine learning applications, including tools such as 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.

For all roles in all locations, we offer a competitive, industry-benchmarked salary. To find out more about the package provided at each location, please visit: https://group.springernature.com/gp/group/careers/current-opportunities/technology-hub

Springer Nature Skills associated with this Job Profile include

SN-Software Engineering & Systems Integration, SN-Product Development & Delivery, SN-Process & Systems Design, SN-Communicates Effectively, SN-Tech Savvy, SN-Manages Complexity, SN-Process Optimization, SN-Storytelling, SN-Big Data Management, SN-Data Security & Governance.

#LI-AR1

We are an ambitious and dynamic organisation, and home to some of the best-known names in research, educational and professional publishing. Working at the heart of a changing industry, we are always looking for great people who care about delivering quality to our customers and the communities we work alongside.

In return, you will find that we open the doors to discovery for all our employees – offering opportunities to learn from some of the best in the business, with a culture that encourages curiosity and empowers people to find solutions and act on their instincts.

Whether you are at the beginning of your career or are an experienced professional, we invite you to find out more about the roles we offer and explore our current vacancies.

We are a global and progressive business, founded on a heritage of trusted and respected brands – including Springer, founded in 1842, Macmillan, founded in 1843 and Nature, first published in 1869.

Nearing two centuries of progress and advancement in science and education have helped shape the business we are today. Research and learning continues to be the cornerstone of progress, and we will continue to open doors to discovery through trusted brands and innovative products and services.

Springer Nature Group was created in May 2015 through the combination of Nature Publishing Group, Macmillan Education and Springer Science+Business Media.