Senior Physics-machine Learning Engineer - Cae

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA

Develop a Physics-AI framework (NVIDIA PhysicsNemo) for constructing digital twins and machine learning simulation surrogates for science and engineering problems, collaborating with internal teams and external users, and staying updated on the latest deep learning research to enhance NVIDIA's technologies.

What you'd actually do

  1. Collaborate with some of the brightest minds in a leading AI company to develop a leading Physics-AI framework, NVIDIA PhysicsNemo, for our academic and industrial partners to construct digital twins and machine learning simulation surrogates for real world science and engineering problems
  2. Work with internal teams at Nvidia and external users to validate the product with industrial applications
  3. Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies with focus on simulations

Skills

Required

  • BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience
  • 5+ yrs of relevant experience
  • Strong Python programming skills
  • Familiarity with containers, numeric libraries, modular software design
  • Good knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.)
  • experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)
  • Experience in solving and using machine learning for real world problems involving scientific/engineering simulations (multi-physics applications in CFD, structural, thermal, electrical, electromagnetics, optics, acoustics etc. for various industries such as automotive, aerospace, machinery, medical, energy, computers, semiconductors, consumer goods etc.)
  • Strong analytical skills with bias for action
  • Good time management and organization skills
  • Solid written and oral communications skills
  • Good teamwork and interpersonal skills

Nice to have

  • Experience with scientific visualization
  • Work with multi-node systems with data-parallel and model parallel programming experience
  • Experience with CUDA
  • Usage of nonlinear simulation tools and techniques
  • usage of major simulation codes (opensource and/or commercial)
  • Development and applications of the new architectures and algorithms on industry scale problems
  • Published papers in the field of AI in scientific computing

What the JD emphasized

  • PhD preferred
  • Experience in solving and using machine learning for real world problems involving scientific/engineering simulations
  • Published papers in the field of AI in scientific computing

Other signals

  • develop a leading Physics-AI framework
  • construct digital twins and machine learning simulation surrogates
  • implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies