Description
NVIDIA is seeking a Solutions Architect to work with academia and research partners. As a Solutions Architect, you will be the primary technical contact for customers and engage deeply with researchers and application developers to drive the adoption of NVIDIA technology.
Responsibilities:
- Partner directly with leading research labs, researchers, and university faculty as a trusted technical advisor: develop a keen understanding of their scientific goals and drive joint research projects at supercomputing scale.
- Identify and accelerate high-impact workloads by integrating NVIDIA's frameworks, libraries, and core software stack into research projects, and help researchers amplify their impact through publications, conference presentations, and technical content.
- Advocate for accelerated computing and Deep Learning, and deliver hands-on trainings, workshops, lectures, and demonstrations across NVIDIA's platforms, and mentor power users to become NVIDIA champions.
- Track emerging research trends and turn gaps between researcher needs and NVIDIA's offerings into prototypical solutions and direct feedback to NVIDIA Engineering.
- Maintain deep expertise in your domain while staying versatile across NVIDIA's full platform: GPUs, CPUs, networking, and software
Requirements:
- A graduate degree from a leading university in a STEM related discipline.
- 5+ years of hands-on experience running the large language model lifecycle across multi-node systems: training, fine-tuning, inference, serving, and/or agentic workflows.
- Strong collaboration and communication skills, with the ability to build relationships with academic and research stakeholders, and to communicate complex ideas clearly to both expert and non-expert audiences.
- Action oriented, analytical, self-motivated, and a passionate learner, with excellent organization skills to work in a heavily multi-tasked environment.
- Fluent in English, both oral and written, and comfortable working in Python.
Preferred Qualifications:
- A PhD from a leading university in a STEM related discipline, with 3+ years of research on large language models or foundation models and their applications.
- A track record of thought leadership: high-impact publications, talks at academic conferences and workshops, as well as good understanding of scientific policy engagement, grant processes, or national/European research program structures.
- Experience with NVIDIA's AI software stack, powered by CUDA and CUDA-X libraries, e.g. NVIDIA AI Enterprise, NeMo Framework, Megatron Bridge, NIM, TensorRT-LLM, Dynamo, NeMo Agent Toolkit, and Triton Inference Server, as well as the Nemotron open-model methodology.
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