Solutions Architect

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. Job Data by YubHub .