Team Leader Scientific Computing & AI/HPC Infrastructure (m/f/d)

The Fraunhofer Society is one of the world's leading organisations for application-oriented research. 75 institutes develop groundbreaking technologies for our economy and society – more precisely: 32 000 people from technology, science, administration and IT. You know, who comes to Fraunhofer wants and can change something. For yourself, for us and the markets of today and tomorrow. Designing technologies for tomorrow: this is our mission at the Fraunhofer Institute for Optronics, System Technology and Image Evaluation IOSB. We research, develop and evaluate new visual systems and ensure the optimal use and networking of sensors in order to optimally process and evaluate the data streams produced. We support people in decision-making, process optimization and intelligent control of autonomous systems. Where research is applied, change is created – shape the future with us! Your mission At IOSB you build a new team that develops, implements and reliably operates an institute-wide, future-proof AI and scientific computing infrastructure. You thus strengthen the technological basis for data-intensive AI research and ensure the efficient, demand-oriented access of the scientific departments to high-performance computing and AI computing resources. As an interface between research needs and infrastructure, you play a central role in the scientific performance of the institute.

Leadership & Development Construction and management of the new team »Scientific Computing Infrastructure« Development of a long-term strategy plan for AI and HPC infrastructure at IOSB Evaluation of new technology trends (AI hardware, software stacks) and derivation of concrete action recommendations Responsibility for budget planning, investment decisions and resource management Planning and control of larger infrastructure projects from design to commissioning Technical focus Conception, development and development of scalable GPU clusters for AI workloads (training, inference, distributed computing) Design and implementation of high-bandwidth storage systems and network architectures for data-intensive research Ensuring a performant, safe and efficient operation of computing resources for AI and simulation Building and optimizing automated deployment and operating processes for AI and HPC workloads Interface to Science Close cooperation with scientific departments for the collection and implementation of AI and HPC requirements Development of best practices, training concepts and self-service solutions for users Creation of technical documentation, standards and architectural documentation

A completed university degree in Computer Science, Engineering, Mathematics or Similar Multiannual experience in the operation or management of HPC or AI computing infrastructures, ideally in a scientific or research environment Understanding AI workloads, GPU computing and distributed training Very good knowledge of modern HPC and AI software stacks (e.g. cluster scheduler, containerization, CUDA, PyTorch/TensorFlow ecosystem) Experience with automation and infrastructure as code (e.g. Ansible, Kubernetes, Slurm) Experience in technical and disciplinary leadership of technical teams Ability to strategically evaluate complex technical solutions and to translate them into understandable decision bases Understanding the requirements of scientific research and joy in cooperation with interdisciplinary teams Very good knowledge of German and English

A varied activity at the interface between science and practice – with direct reference to future technologies and socially relevant applications. Free space for development and the possibility of actively introducing your own ideas and projects. Excellent technical equipment and optimal working conditions Motivated colleagues who inspire each other through their interdisciplinary and international composition Attractive framework conditions for the reconciliation of work and private life (e.g. flexible working hours within a sliding time model, individual home office regulations) Individual career paths through training and development opportunities (e.g. funding and development programme »Fraunhofer TALENTA« for female scientists) In the case of interest and qualification, there is the possibility of promotion Free parking and an efficient charging infrastructure for electric vehicles A canteen and nearby shopping facilities A very good connection to the ÖPNV and a grant to the Deutschlandticket