For around 15 years, Rhine-Waal University of Applied Sciences has provided an innovative, interdisciplinary and international education to young minds from around the world. Located in the Lower Rhin region of Germany, we offer a total of 37 undergraduate and postgraduate degree programmes in four multidisciplinary faculties: Technology and Bionics, Life Sciences, Society and Economics, and Communication and Environment. International collaboration is a strength of ours, seen and felt in our network of over 90 partner universities in 38 countries. Rhine-Waal University of Applied Sciences is connected to the larger world, but also deeply rooted in its Dutch-German EUREGIO regional home.

The collaborative project SALAMI.Team (Scalable Language Model Infrastructure), led by Hochschule Rhein-Waal, aims to establish and explore an NRW-funded, cross-scale AI research infrastructure that serves as the foundation for a regional innovation ecosystem for artificial intelligence in small and medium-sized enterprises. The technological spectrum ranges from high-performance GPU servers (NVIDIA DGX B300) and workstations (RTX Pro 6000) to compact embedded systems. In concrete implementation projects, the cooperation partners jointly develop AI applications in the fields of agricultural robotics, precision agriculture, e-government, psychology, and computer-vision-based damage analysis. Open-weight AI models are preferentially optimized and scaled for specific applications. The goal is minimal consumption of storage, computing power, and energy in order to significantly simplify the local deployment of models.

Join our team and help strengthen our university in the Faculty of Communication and Environment, Kamp-Lintfort Campus, in the following position, to be filled as soon as possible

AI Engineer / Expert in AI Systems and AI Infrastructure (SALAMI.Team)

Reference Number 05/F4/26

German TV-L pay scale level EG 13 | fixed-term contract until 31.05.2029 project-based | part-time position with an average of 31,86 weekly hours.

YOUR FUTURE RESPONSIBILITIES

• Design, implementation and productive deployment of novel AI processing pipelines (foundation models, LLMs, computer vision models) for different use cases and hardware scales of the AI research infrastructure; for some of the required methods no standard market solutions exist, so previously unavailable solution paths are developed independently
• Modification and extension of existing IT procedures through technical adaptation, optimisation and scaling of models (incl. quantisation, distillation, resource-minimal local operation) as well as design, setup and productive commissioning of RAG systems, AI agents and reinforcement-learning-based systems, including selection, integration and protection of the system components (e.g. for robotics and automation applications)
• Dimensioning, setup, configuration, maintenance and operation of the GPU/HPC infrastructure (multi-GPU, NVLink, CUDA) and the associated Linux server environment
• Assurance of scalability, resilience, IT security and GDPR compliance of the systems in operation
• Technical analysis of the requirements arising from the implementation projects, derivation of viable solution concepts and evaluation and selection of suitable open-weight models and frameworks
• Technical consulting of project partners from academia and small and medium-sized enterprises on feasibility, architecture and transfer into operation, including technical support of transfer formats (e.g. workshops, hackathons)
• Technical quality assurance, test design and documentation as well as preparation and provision of the results as open sourc

YOUR SKILLS AND QUALIFICATIONS

• Completed relevant academic university degree (Master or equivalent degree) in computer science, data science, electrical engineering, mechanical engineering or a comparable field and relevant experience. A relevant doctorate is an advantage
• Practical experience in implementing AI projects – including within the context of studies, a doctorate, project or thesis work, internships, or open-source contributions. Relevant professional experience in the independent development and operation of AI systems is an advantage but not a strict requirement
• Required:
• Solid knowledge of machine learning / deep learning, in particular of foundation models (LLMs, computer vision)
• Proficiency with common AI frameworks (e.g. PyTorch, Hugging Face, LangChain) and with Python
• Experience with AI agents and/or reinforcement learning
• Knowledge of Linux server administration and of network/VPN configuration
• Desirable:
• Knowledge of model adaptation, optimisation and distillation as well as of the setup and operation of RAG systems
• Knowledge of building and operating GPU/HPC infrastructure (multi-GPU, NVLink, CUDA)
• Knowledge of robotics frameworks (ROS/ROS2) and embedded systems (e.g. NVIDIA Jetson)
• Basic knowledge of the applicable legal frameworks (GDPR, AI Act (EU) 2024/1689, DSG NRW) and of open-source/open-weight licensing
• Basic knowledge of IT security and system maintenance (e.g. patch/update management), or willingness to acquire it
• Experience with agile, prototypical software development (e.g. Scrum/Kanban, iterative prototype development) as well as with version control and technical project documentation (e.g. Git, CI/CD). Ability to independently develop viable solution concepts for novel problems without an available standard solution, to weigh up technical alternatives and to plan, steer and document the implementation independently. Experience in the technical design and support of training and transfer formats (e.g. workshops, hackathons) for diverse target audiences, including non-technical stakeholders from business and society.
• Strong communication skills when working with interdisciplinary teams from higher education and industry, as well as the ability to present and convey complex technical content in a way that is appropriate for different audiences. A team-oriented working style and willingness to coordinate closely with project partners, students, and regional stakeholders. Independent and structured working approach, even in a dynamic project environment.
• Ability to independently steer the assigned work packages and to decide between technical alternatives within the scope of the delegated decision-making authority, as well as experience in the technical guidance of student assistants and project staff.
• German language skills at B1 level, English language skills at B2 level
• Gender and diversity competence

WHAT WE OFFER YOU

Diversity | Internationality | Certified as a family-friendly university | Mobile working as well as home office | University sports | Collegial, open working atmosphere| Exciting and varied range of tasks | Personal responsibility and creative freedom | opportunities for personal and professional development

Rhine-Waal University of Applied Sciences is committed to the professional development and advancement of women. Female candidates are expressly welcomed and encouraged to apply. In accordance with the Gender Equality Act of North Rhine-Westphalia (Landesgleichstellungsgesetz NRW), in cases of equal suitability, aptitude and professional experience, female candidates shall be given preferential consideration over male candidates for vacancies in areas with proportionally fewer female employees, provided there are no specific, overriding reasons for giving preference to a specific male candidate.

In the event of equal suitability, preferential consideration will also be given to disabled candidates or candidates recognised as such by virtue of Section 2 (3) of the German Code of Social Law, Book IX (SGB IX).

• Please submit your application through the following link: and we look forward to receiving your application by no later than 28-10-2026.

For questions regarding the application process, please contact Mr. Ewert at +49(0)2821 80673-175.