NVIDIA

Senior Research Scientist, AI for Climate and Weather Simulation

NVIDIA

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $184,000 - $356,500 per year

Job Level

Senior

Tech Stack

PyTorch

About the role

  • NVIDIA Research’s AI Climate and Weather Simulation Team is looking for a senior research scientist.
  • Mission is to re-imagine technology across the Earth System Modeling stack using new ideas in AI on applied topics such as state estimation, convection-permitting AI atmosphere or ocean simulation, steerable climate state sampling for advanced informatics, multi-component autoregressive Earth System prediction, reasoning over multi-modal climate data -- and related frontier topics.
  • Propose, research, prototype and test innovative research ideas.
  • Publish groundbreaking work at top conferences and journals.
  • Collaborate with other research team members, internal product teams, external researchers and mentor interns.
  • Make good use of top-of-the-line NVIDIA GPUs at scale for cutting edge research at the intersection of AI and climate science.
  • Help lead technology transfer with engineers around NVIDIA as ideas graduate from research to product.

Requirements

  • Ph.D. in the geophysical sciences, computer science, applied math/statistics, or related fields.
  • At least 4 years of research experience in deep learning, computer vision, generative AI, or related fields.
  • Outstanding research portfolio including multiple first-author publications in reputable conferences or journals that make good use of AI.
  • Excellent taste in problem selection.
  • Proficiency with distributed deep learning training frameworks, e.g., PyTorch.
  • Bonus for CUDA.
  • Excellent software engineering skills and experience in scaling algorithms for high computational loads.
  • Experience developing in a changing software environment and ability to drive research projects end-to-end -- including the messy parts.
  • Preferred: Synergistic expertise in climate domain science, nonlinear physics, and familiarity with associated synthetic and observational datasets and physical simulation systems.
  • Excellent communication & collaboration skills; ability to variably lead or contribute as needed.
  • Drive to transfer technology to products.