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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Solutions Architect, Higher Education and Research, Multimodal and Physical AI - **Company:** Nvidia - **Location:** Reading, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Nvidia CUDA, Microprocessors, Python (Programming Language), Graphics Processing Unit (GPU), TensorRT, Nim (Programming Language) - **Published:** September 2, 2026 - **Apply:** https://uk.indeed.com/viewjob?jk=7895b510454258af ## About the Role * A graduate degree from a leading university in a STEM related discipline. * 5+ years in the multimodal and world model lifecycle on multi-node GPU systems: video and image data curation at scale, pre-training and post-training, evaluation, and efficient inference. * 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 in the domain. * 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 stack for visual and multimodal AI, built on CUDA and CUDA-X, including Cosmos world foundation models, NeMo Framework and Megatron for multimodal model training, multimodal Nemotron methodology, Isaac robotics platform, NuRec for neural reconstruction, TensorRT and NIM for deployment, and domain frameworks such as MONAI for medical imaging. ## 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, robotics, Multimodal AI and Physical AI, 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 ## Related Videos - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [On developing smartphones on wheels](https://www.wearedevelopers.com/videos/258-on-developing-smartphones-on-wheels) - [Tour de Force: Open-Source LLM Inference Optimization from Simple to Sophisticated](https://www.wearedevelopers.com/videos/100099-tour-de-force-open-source-llm-inference-optimization-from-simple-to-sophisticated) - [Nemotron: NVIDIA's open model strategy for developers](https://www.wearedevelopers.com/videos/100064-nemotron-nvidia-s-open-model-strategy-for-developers) - [Trends, Challenges and Best Practices for AI at the Edge](https://www.wearedevelopers.com/videos/630-trends-challenges-and-best-practices-for-ai-at-the-edge) - [Efficient deployment and inference of GPU-accelerated LLMs​](https://www.wearedevelopers.com/videos/929-efficient-deployment-and-inference-of-gpu-accelerated-llms) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [ I Gave a Video Editor More Autonomy Than a Trading Bot. 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