Senior Solutions Architect, Higher Education and Research, Multimodal and Physical AI

Your profile

What we need to see:

• A graduate degree from a leading university in a STEM related discipline or equivalent experience.
• 5+ years across 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

Ways to stand out from the crowd:

• 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.

As a Solutions Architect, there is travel involved (20% of the working time), as often the best way to figure things out is a face-to face meeting, but the job is not life on the road. We make heavy use of conferencing tools, and you are empowered to figure out how to get the job done and do what it takes to make our customers successful

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Source: Statistisches Bundesamt (Destatis), table; dl-de/by-2-0; StarIn's calculation