1 month ago
Remote, United Kingdom +2 moreSenior
Responsibilities
- Serve as a trusted technical advisor to research labs, researchers, and university faculty.
- Develop and accelerate large-scale scientific workloads by integrating NVIDIA frameworks, libraries, and software.
- Drive joint research projects and support publications, conference presentations, trainings, workshops, lectures, and demonstrations.
- Track research trends, develop prototype solutions, and provide feedback to NVIDIA Engineering.
- Maintain expertise across NVIDIA GPUs, CPUs, networking, and software while mentoring advanced users.
Requirements
- Graduate degree in a STEM-related discipline.
- At least 5 years of hands-on experience with the large language model lifecycle across multi-node systems, including training, fine-tuning, inference, serving, and/or agentic workflows.
- Strong collaboration, communication, analytical, organizational, and relationship-building skills for working with academic and research stakeholders.
- Fluency in written and spoken English and comfort working in Python.
- Preferred qualifications include a PhD, 3+ years of research on large language models or foundation models and their applications, high-impact publications or conference talks, knowledge of scientific policy and grant processes, and experience with NVIDIA’s AI software stack.
Benefits
- The role involves approximately 30% travel and otherwise makes extensive use of conferencing tools.
- Employees are empowered to determine how to accomplish the work and support customer success.
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.