Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Python @ 7
Algorithms @ 4
Machine Learning @ 4
TensorFlow @ 4
Communication @ 4
Mathematics @ 4
Parallel Programming @ 4
PyTorch @ 4
CUDA @ 4
Deep Learning @ 4
AI @ 4
Reinforcement Learning @ 4
HPC @ 4
JAX @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
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. We are building an AI framework to solve cutting-edge science and engineering problems: weather/climate, product design, digital twins, molecular dynamics, novel materials, accelerated drug development, and more.
Responsibilities
- Collaborate with internal teams and external partners to develop a Physics-AI framework (NVIDIA PhysicsNemo) for constructing 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 deep learning innovations; implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies with a focus on simulations.
Requirements
- 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, and 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 developing or using major deep learning frameworks (PyTorch, TensorFlow, JAX).
- Experience applying machine learning to real-world problems involving scientific/engineering simulations (multi-physics applications in CFD, structural, thermal, electrical, electromagnetics, optics, acoustics, etc.) across industries such as automotive, aerospace, medical, energy, semiconductors, consumer goods.
- Strong analytical skills and bias for action; good time management and organization skills for a fast-paced environment.
- Solid written and oral communication skills; good teamwork and interpersonal skills.
Ways to stand out
- Experience with multi-node systems, data-parallel and model-parallel programming.
- Experience with CUDA.
- Usage of nonlinear simulation tools and major simulation codes (open-source and/or commercial) and development/applications of new architectures and algorithms on industry-scale problems.
- Published papers in the field of AI in scientific computing.
Compensation and Benefits
- Base salary ranges: 152,000 USD - 241,500 USD for Level 3; 184,000 USD - 287,500 USD for Level 4.
- Eligible for equity and benefits (link to NVIDIA benefits).
Additional information
- Applications accepted at least until July 9, 2026.
- This posting is for an existing vacancy.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer and committed to an inclusive work environment.