2 months ago
Munich, GermanySenior
Responsibilities
- Act as a trusted technical advisor to research labs, researchers, and university faculty.
- Drive joint research projects and accelerate high-impact workloads on multi-node GPU systems.
- Integrate NVIDIA frameworks, libraries, and core software into research projects.
- Support publications, conference presentations, technical content, trainings, workshops, lectures, and demonstrations.
- Advocate for accelerated computing, robotics, multimodal AI, and physical AI across NVIDIA platforms.
- Develop prototype solutions from researcher needs and communicate feedback to NVIDIA Engineering.
- Maintain expertise across GPUs, CPUs, networking, and software while mentoring power users.
- Travel approximately 20% of working time for customer and research-partner engagements.
Requirements
- Graduate degree in a STEM-related discipline from a leading university or equivalent experience.
- At least 5 years of experience across the multimodal and world model lifecycle on multi-node GPU systems.
- Experience with large-scale video and image data curation, pre-training, post-training, evaluation, and efficient inference.
- Strong collaboration and communication skills with academic and research stakeholders.
- Fluent written and spoken English and comfort working in Python.
- PhD in a STEM-related discipline and 3+ years of domain research experience are preferred.
- Preferred experience includes high-impact publications, academic conference talks, scientific policy engagement, grant processes, or national and European research programs.
- Preferred experience with NVIDIA’s visual and multimodal AI stack, including CUDA, CUDA-X, Cosmos, NeMo Framework, Megatron, Nemotron, Isaac, NuRec, TensorRT, NIM, and MONAI.
Benefits
- Approximately 20% travel with extensive use of conferencing tools and flexibility to determine how to support customers effectively.
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.