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Nvidia Robotics Solution Architect – DNN Training Vision-Language-Action Models 
United Kingdom, England, Southampton 
449668802

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Posted 6 Days Ago
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What you will be doing:
  • Serve as the primary technical expert between NVIDIA and our customers, understanding their technology and provide the best AI solutions/ guidance on training process in terms of tools and methodology

  • Build proof-of-concepts and demonstrations that highlight the power of NVIDIA AI platforms in robotics

  • Partner with developers, researchers, technology specialists, IT professionals, and executives to facilitate the integration of NVIDIA technology

  • Work with Engineering, Product and Sales teams to develop, plan best suitable solutions for customers. Enable development and growth of product features through customer feedback and proof-of-concept evaluations.

What we need to see:
  • MS/PhD or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering fields.

  • Deep expertise in AI/Deep Learning, with hands-on experience in training or optimizing VLMs for production

  • Expertise with deep learning frameworks for training VLMs (PyTorch, Nemo), and/or experience with such model's optimization methods and tools (TensorRT and Triton Inference Server).

  • Excellent verbal, written communication, and technical presentation skills in English.

  • 5+ years' work or research experience with Python/ C++ / other software development

  • AI passionate with a growth mindset, ability to collaborate effectively with different teams (Engineering, Product, Sales, Marketing) in a rapid evolving environment while continuously learning and sharing insights.

Ways to Stand Out from The Crowd:
  • Familiarity with Cosmos (e.g. Cosmos-Reason) and Isaac GR00T family of models.

  • Familiarity with robotics simulation environments (Isaac Sim, Isaac Lab, MuJoco, etc.).

  • Experience in large scale training / understanding of modern model, data, expert, context parallel training techniques.

  • Track record in Neural Networks inference optimization for Physical AI use cases