1 day ago
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
Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.