Dev​/MLOps Engineer; m​/f​/d

Job Location:

Global

As the German National Library of Science and Technology, our future-oriented services ensure the infrastructural requirements for a high-quality supply of information and literature for research in science and industry. With the Open Research Knowledge Graph (ORKG), we are working to revolutionise the exchange and use of scientific knowledge in the digital age.

The Technische Informationsbibliothek (TIB) – Leibniz Information Centre for Science and Technology – Program Area D, Open Research Knowledge Graph, is seeking a Dev/MLOps Engineer (m/f/d) to join the Artificial Intelligence for Scholarly Communication Research Group (Prof. Dr. Sahar Vahdati) as of 1 September 2026. The position is initially limited to the project duration of three years, with a possibility for extension.

The regular weekly working hours are 39.8 hours (full-time). The position is generally suitable for part-time work.

The role is expected to be carried out on site in Hanover, with mobile work possible to a certain extent, subject to operational requirements. The remuneration is based on pay scale group 13 of the collective agreement for the public service of the German states (TV‑L).

Your role:

We are seeking a Dev Ops/MLOps Engineer interested in building, optimizing and operating cloud-native infrastructure for general‑purpose AI assistants at scale within the European Open Science Cloud (EOSC) ecosystem.

The successful candidate will have a strong background in software delivery, cloud-native platforms, containerization, orchestration and automation, as well as practical experience with operating reliable infrastructure for AI‑ and data‑intensive workloads. The role focuses on supporting the cloud-native migration, building and maintaining software delivery and observability platforms and ensuring scalable, secure and reliable deployment environments.

Key responsibilities include:

• Designing and developing containerised architectures optimized for EOSC cloud environments.
• Building and operating high-performance compute environments to ensure reliable, low‑latency operation of general-purpose AI assistants.
• Developing automated software delivery life cycles and CI/CD pipelines for frequent and reliable deployments across distributed ecosystems.
• Implementing monitoring, logging and alerting frameworks to ensure the health, performance and security of services within the EOSC ecosystem.
• Configuring and maintaining secure access controls and AAI integrations, including federated authentication and authorization mechanisms.

For further information or to express interest, please contact Prof. Dr. Sahar Vahdati, head of the Artificial Intelligence for Scholarly Communication Research Group, by e‑mail dati.