As one of Europe’s leading facilities for high-performance computing, HLRS is a diverse community of scientists, engineers, and other professionals focused on discovering and developing new applications of powerful digital technologies and computer science methods.
The High-Performance Computing Centre Stuttgart (HLRS) was founded as Germany’s first federal high-performance computing (HPC) centre. It operates one of the fastest supercomputers in the world. It offers various HPC solutions and services for universities, research institutions, and industry. Furthermore, HLRS is a worldwide leader in engineering and global system sciences. Staff scientists at HLRS investigate emerging technologies such as Artificial Intelligence (AI), Cloud Computing, and Quantum Computing (QC) towards realising hybrid workflows and lowering the hurdle for non-experts using HPC technologies. In this context, HLRS is significantly involved in international and national research projects across the abovementioned research areas.

SHAPING THE FUTURE OF AI IN HPC

We seek a highly motivated AI Application Support Engineer to assist users in effectively deploying, managing, and optimizing AI workloads within the AI Factory HammerHAI at HLRS. This role will provide hands-on support to AI users, troubleshoot issues, and ensure best practices for AI development and deployment in high-performance computing environments. The successful candidate will work closely with AI researchers, software developers, and system administrators to ensure a seamless AI application experience. This position requires expertise in AI and, ideally, in high-performance computing systems.
In this context, we are looking for a

• Provide one-on-one user support for external users regarding AI and hybrid HPC-AI workflows (simulations).
• Collect and analyse user requirements to tailor AI software architectures and stacks.
• Collaborate with industry partners and researchers to develop next-generation AI solutions leveraging AI-optimised supercomputing resources.
• Benchmark, analyse and optimise AI workflows on HPC systems using profiling tools.
• Contribute to user-oriented documentation and scientific publications (e.g., conferences, white papers, journals).