Senior Physics-Machine Learning Engineer - CAE

Reposted Yesterday
Santa Clara, CA, USA
In-Office
152K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Develop and validate NVIDIA PhysicsNemo, a Physics-AI framework for digital twins and simulation surrogates. Collaborate with internal teams and external partners, implement state-of-the-art deep learning architectures for scientific/engineering simulations, and stay current with research to improve production-ready ML and HPC solutions.
Summary Generated by Built In

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 PhysicsNemo, 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+ 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.) with 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.)

  • 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 communications 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 (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

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world.

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.

Applications for this job will be accepted at least until July 9, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

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.

#deeplearning

Skills Required

  • BS or MS degree in computer science, mathematics, computational science/engineering, or related field (PhD preferred)
  • 5+ years of relevant experience
  • Strong Python programming skills
  • Familiarity with containers and numeric libraries (e.g., NumPy); modular software design
  • Good knowledge of state-of-the-art DNN architectures and ML techniques (graph networks, diffusion models, reinforcement learning)
  • Experience developing or using major deep learning frameworks (PyTorch, TensorFlow, JAX)
  • Experience applying machine learning to real-world scientific/engineering simulations (multi-physics: CFD, structural, thermal, electrical, electromagnetics, optics, acoustics, etc.)
  • Strong analytical skills and bias for action
  • Good time management and organization skills for fast-paced environments
  • Solid written and oral communication skills; teamwork and interpersonal skills
  • Experience with scientific visualization
  • Multi-node systems experience with data-parallel and model-parallel programming
  • Experience with CUDA and nonlinear simulation tools; use of major simulation codes (open-source or commercial)
  • Published papers in AI for scientific computing

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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