4 days ago
Munich, GermanySenior
Responsibilities
- Advise research labs, researchers, and university faculty on scientific goals, AI workloads, accelerated computing, and NVIDIA technologies.
- Drive joint research projects and integrate NVIDIA frameworks, libraries, and software into large-scale research workloads.
- Support LLM training, fine-tuning, inference, serving, and agentic workflows across multi-node systems.
- Deliver hands-on trainings, workshops, lectures, and demonstrations, and mentor power users.
- Track research trends, develop prototypes to address researcher needs, and provide feedback to NVIDIA Engineering.
- Promote accelerated computing and deep learning through publications, conference presentations, and technical content.
Requirements
- Graduate degree in a STEM-related discipline.
- At least 5 years of hands-on experience running the LLM lifecycle across multi-node systems, including training, fine-tuning, inference, serving, and/or agentic workflows.
- Strong collaboration, communication, analytical, organizational, and relationship-building skills with academic and research stakeholders.
- Fluency in written and spoken English and comfort working with Python.
Benefits
- Approximately 30% travel is expected, with extensive use of conferencing tools and flexibility in how work is completed.
- Base salary is determined by location, experience, and other objective job-related factors, with published ranges for Germany and France.
Tech Stack
NimPython
Categories
Solutions Engineering
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.