2 months ago
Zürich, SwitzerlandSenior
Responsibilities
- Advise research labs, researchers, and university faculty on NVIDIA technologies and architectures.
- Drive joint research projects and accelerate multimodal and physical AI workloads on multi-node GPU systems.
- Integrate NVIDIA frameworks, libraries, and core software into research projects.
- Support publications, conference presentations, technical content, and research impact.
- Deliver hands-on trainings, workshops, lectures, demonstrations, and user mentoring.
- Track emerging research trends, develop prototype solutions, and communicate product gaps to NVIDIA Engineering.
- Maintain expertise across NVIDIA GPUs, CPUs, networking, and software platforms.
Requirements
- Graduate degree in a STEM discipline or equivalent experience.
- At least 5 years of experience across the multimodal and world model lifecycle on multi-node GPU systems, including data curation, pre-training, post-training, evaluation, and efficient inference.
- Strong collaboration, communication, analytical, organizational, and relationship-building skills.
- Fluent written and spoken English and comfort working in Python.
Benefits
- Approximately 20% travel is required.
- The role uses conferencing tools and supports flexible ways of working to serve customers.
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.