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Senior Physics-Machine Learning Engineer - CAE

Job in Santa Clara, Santa Clara County, California, 95053, USA
Listing for: NVIDIA
Full Time position
Listed on 2026-07-10
Job specializations:
  • Software Development
    Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Data Scientist
Salary/Wage Range or Industry Benchmark: 152000 USD Yearly USD 152000.00 YEAR
Job Description & How to Apply Below

NVIDIA’s deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start‑ups, and industry, including the world’s largest Internet companies. We need passionate and creative people to help us on building a AI framework that will solve the toughest and most relevant problems of humanity and problems that are at the cutting edge of science & engineering: weather/climate challenges, product design, digital twins, molecular dynamics, novel materials, accelerated drug development, etc.

What

you'll be doing:
  • Collaborate with some of the brightest minds in a leading AI company to develop a leading Physics‑AI framework, NVIDIA Physics Nemo, for our academic and industrial partners to construct digital twins and machine learning simulation surrogates for real world science and engineering problems.

  • Work with internal teams at Nvidia and external users to validate the product with industrial applications.

  • 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.

What we need to see:
  • BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience.

  • 5+ years 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.) with experience in developing or using major deep learning frameworks (PyTorch, Tensor Flow, 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.).

  • Experience with scientific visualization is a big plus.

  • Strong analytical skills with bias for action.

  • Good time management and organization skills to thrive in a fast paced, dynamic environment.

  • Solid written and oral communication skills. Good teamwork and interpersonal skills.

Ways to stand out from the crowd:
  • 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 (open‑source 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.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering an inclusive 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.

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Position Requirements
10+ Years work experience
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