MLOps Engineer: Cloud ML Pipelines & GenAI Deployments

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

Job summary

Springer Nature is seeking an experienced MLOps Engineer to join the SN AI Lab in Groningen. You will design, deploy, and scale AI solutions across cloud environments, bridging ML development and production operations to ensure reliability and governance.

The role emphasizes end-to-end ML lifecycle management, observability, and collaboration with cross-functional teams to deliver impactful AI capabilities at scale.

Qualifications

• Proven experience delivering software with Python and modern engineering practices.
• Experience with GitHub, Docker, and ML frameworks like PyTorch or TensorFlow.
• Hands-on cloud experience with Azure, AWS, or GCP and building APIs with FastAPI or similar.

Responsibilities

• Design, build, and scale MLOps platforms and pipelines for reliable ML delivery.
• Implement CI/CD, monitoring, and automation to improve velocity and resilience.
• Ensure governance, data security, and responsible AI practices across platforms.
• Mentor engineers and share knowledge on MLOps and AI tooling.

Skills

Python

GitHub

Docker

PyTorch

TensorFlow

FastAPI

CI/CD

Observability

MLOps

LLM deployment

Education

Software Engineering

Computer Science

Artificial Intelligence

Tools

GitHub

Langfuse

FastAPI

Langfuse

Job description

Springer Nature is seeking an experienced MLOps Engineer to join the SN AI Lab in Groningen. You will design, deploy, and scale AI solutions across cloud environments, bridging ML development and production operations to ensure reliability and governance.

The role emphasizes end-to-end ML lifecycle management, observability, and collaboration with cross-functional teams to deliver impactful AI capabilities at scale.