Tokyo NVIDIA

NVIDIA is a world leader in computer graphics, artificial intelligence, and accelerated computing. For over 25 years, NVIDIA has been at the forefront of research and engineering around the greatest advances in technology. Our history of innovation drives us to solve the world's hardest problems.

We are now seeking a Solution Architect to support Japanese manufacturing companies adopt GPU-acceleration and AI for Chemical and Materials Science. The use of AI for discovering novel chemicals, materials, and formulations is a growing area in Industry and Academia. We need someone with domain knowledge and great communication skills to be a trusted technical advisor to our customers and work on exciting projects focused on Industrial High-Performance Computing (HPC) and AI for Chemistry and Materials Science.

What You'll Be Doing

  • Be a technical expert with vision on integrating NVIDIA GPU-accelerated tools and microservices such as ALCHEMI and our CUDA-X libraries into Industrial HPC, Chemistry, Material Science, and Semiconductor Manufacturing workflows.
  • Support the business development team in guiding the customer through the sales process for NVIDIA's platform of GPU compute systems and acceleration software. Be responsible for the technical relationship and assist our customers and partners in developing innovative products using NVIDIA technologies.
  • Dynamically engage with developers, scientific researchers, and data scientists to understand their goals, strategies, and technical needs, and help to define and deliver high-value solutions that meet these needs. Answer questions and provide mentorship – you will help them build their GPU compute infrastructure and get the most out of their investment.
  • Document what you know, and guide others. This can vary from building targeted training for partners and other Solution Architects, to writing whitepapers, blogs, and wiki articles, to working through challenging problems with a partner on a whiteboard.
  • Keep up-to-date on the latest techniques in AI for Chemistry and Materials Science, including atomistic simulation, machine learning interatomic potentials (MLIPs), graph neural networks (GNNs) for property prediction, and structural generative AI models.

What We Need To See

  • Excellent verbal, written communication, and technical presentation skills in Japanese. Business level English communication is also a requirement.
  • BS or MS in Computational Chemistry, Physics, Computer Science, or related field (or equivalent experience)
  • 5+ years of industry or academic experience in the manufacturing ecosystem, applying the latest advances in AI for Chemical and Material Science
  • Strong fundamentals in programming, optimizations and software design, especially in Python and C++
  • Ability to multitask effectively in a dynamic environment.
  • Strong analytical and problem-solving skills.
  • Proactive and have a strong desire to share knowledge with clients, partners and co-workers.

Ways To Stand Out From The Crowd

  • Hands-on experience with CUDA and PyTorch
  • Experience developing or using Machine Learning Interatomic Potential (MLIP) models for chemical and materials discovery.
  • Working knowledge running MD and DFT simulations.
  • Familiarity with Graph Neural Networks (GNNs) for property prediction of molecules, polymers, and formulations.

Widely considered to be one of the technology world's most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family at .

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

JR2008569


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