NAISS, the National Academic Infrastructure for Supercomputing in Sweden, provides academic users with high-performance computing resources, storage capacity, and data services. NAISS is hosted by Linköping University and has 12 partner universities across Sweden.
Mimer offer access to AI-optimised supercomputers and services such as training and support to SMEs, startups, researchers, and government agencies. The aim is to advance innovation, boost the adoption of AI and make Europe a leading AI continent. We are hosted by NAISS in partnership with RISE Research Institutes of Sweden and is part of the EU’s ambitious AI Factories initiative.
Learn more: https://mimer-ai.eu/about-mimer/ , https://www.naiss.se , https://eurohpc-ju.europa.eu/ai-factories_en
The position
Do you want to work at the forefront of Europe’s AI development and contribute to building the next generation of AI infrastructure? We are now looking for a Team Lead for AI Technology & Tools who wants to take a strategic and technically leading role in the development of advanced AI workflows at national and European level. This position offers a unique opportunity to work with large-scale HPC and AI infrastructure within the EuroHPC initiative and to actively contribute to the development of robust, scalable, and responsible AI solutions together with researchers, companies, and public-sector actors.
As Team Lead for AI Technology & Tools, you will be responsible for leading the technical development within the team and contributing to the integration of MIMER’s AI platform into real-world use cases in industry and research. The role combines technical leadership with hands-on operational work and close dialogue with both internal experts and external partners. You will contribute to the development of MIMER’s cloud-native supercomputing environment and federated EuroHPC services, with a focus on robust and efficient AI workflows.
Responsibilities
Technical Leadership and AI Platform
- Drive and develop best practices for training, optimizing, and deploying AI models on HPC and GPU-based systems.
- Provide guidance on performance optimization, scaling, and efficient resource utilization.
- Contribute to architectural and design decisions in cloud-native HPC environments.
MLOps and AI Workflows
- Support organizations in building end-to-end AI pipelines — from data management to deployment.
- Provide advice on reproducibility, version control, and sustainable model lifecycle management.
- Contribute to the integration of AI services into existing research and industrial environments.
Infrastructure and Integration
- Work with hybrid and federated solutions within EuroHPC.
- Support integration between MIMER’s computing resources and external systems.
- Contribute to the development of a coherent European AI capacity.
Collaboration and External Engagement
- Act as a technical counterpart in dialogues with companies and organizations.
- Translate technical capabilities into concrete solutions and use cases.
- Contribute to strengthening the MIMER ecosystem through collaboration and knowledge sharing.
The person we need
We are looking for someone who has:
- A PhD or equivalent experience in AI/ML, HPC, or a related technical field.
- Documented experience in large-scale AI training and GPU-accelerated environments.
- Understanding of distributed training frameworks and performance optimization.
- Experience with MLOps and production-oriented AI workflows in research and/or industry.
- Knowledge of cloud-based, on-premises, and hybrid infrastructure.
- Ability to work in interdisciplinary and international environments.
- Ability to communicate technical solutions to different target groups.
It is particularly meriting if you have:
- Experience with generative AI models, such as LLMs or speech AI.
- Experience with containerized and cloud-native environments.
- Experience with EuroHPC or federated computing environments.
- Experience working with industrial AI solutions in production or regulated environments, or in mission-critical applications.
- Experience in technical leadership or coordination of development teams.
The workplace
You will work at the National Academic Infrastructure for Supercomputing in Sweden that is hosted by Linköping University at Campus Valla. We are a growing organization changing rapidly, which means we offer excellent opportunities for professional development new responsibilities. The centre includes a broad range of staff ranging from system administrators to user support, training and administrative roles. Read more at https://www.naiss.se, https://www.nsc.liu.se.
The employment
Permanent position, full-time, 100%.
The employment entails a position as Applikationsexpert.
Starting date as soon as possible or by agreement.
This position may come to be a security classified position. If so, security screening including a records check will be carried out before any decision on employment is made.
Salary and employment benefits
Linköping University is a Swedish public employer and offers individual salary setting, as well as opportunities to combine parenthood and an active lifestyle with employment.
NAISS offers a possibility of remote work up to 40% of the working time.
More information about employee benefits is available here .
Union representatives
Information about union representatives, see Help for applicants .
Application procedure
Apply for the position by clicking the “Apply” button below. Your application must reach Linköping University no later than 2026-04-30 (CET).
Applications and documents received after the date above will not be considered.
We welcome applicants with different backgrounds, experiences and perspectives - diversity enriches our work and helps us grow. Preserving everybody's equal value, rights and opportunities is a natural part of who we are. Read more about our work with: Equal opportunities .
We look forward to receiving your application!
Linköping university has framework agreements and wishes to decline direct contacts from staffing- and recruitment companies as well as vendors of job advertisements.
URL to this page
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