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# Senior Solutions Architect, Higher Education and Research - Open Models and LLM

- **Company:** Nvidia
- **Location:** Reading, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Nvidia CUDA, Microprocessors, Python (Programming Language), Graphics Processing Unit (GPU), Large Language Models, Deep Learning, Machine Learning Operations, TensorRT, Nim (Programming Language)
- **Published:** August 29, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=7bc5a467c81e3b0c

## About the Role

* 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., * 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.

## Description

* 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 o erings 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


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