MLOps Engineer — AI Platforms & Cloud Automation

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

Job summary

Springer Nature AI Lab (SNAIL) is seeking an MLOps Engineer in Groningen to bridge ML development and production operations, ensuring reliable, scalable AI systems in cloud environments.

You will design deployment pipelines, implement monitoring and governance, and mentor junior engineers while collaborating across teams.

Experience with Python, Docker, FastAPI, and cloud platforms; strong CI/CD and observability are essential.

Qualifications

• Proven experience with Python-based software development and ML engineering.
• Hands-on with cloud platforms (AWS/Azure/GCP) and containerization (Docker).
• Experience building APIs with FastAPI or similar.
• Strong CI/CD, testing, and observability practices for ML deployments.

Responsibilities

• Design, build, and maintain scalable MLOps platforms and deployment pipelines.
• Develop cloud-native services and CI/CD workflows to improve velocity and reliability.
• Implement monitoring, observability, tracing, and performance management for AI systems.
• Drive model lifecycle management, governance, and deployment resilience.
• Contribute to data security, governance, and responsible AI practices.
• Document AI capabilities and share knowledge across the organization.
• Mentor junior engineers in MLOps and AI engineering.
• Stay updated with AI engineering trends to improve platforms.

Skills

Python

GitHub

CI/CD practices

APIs

Education

Bachelor's degree in Computer Science, Software Engineering, AI or related field

Tools

Docker

PyTorch

TensorFlow

FastAPI

Langfuse

AWS

Azure

GCP

Job description

Springer Nature AI Lab (SNAIL) is seeking an MLOps Engineer in Groningen to bridge ML development and production operations, ensuring reliable, scalable AI systems in cloud environments.

You will design deployment pipelines, implement monitoring and governance, and mentor junior engineers while collaborating across teams.

Experience with Python, Docker, FastAPI, and cloud platforms; strong CI/CD and observability are essential.