Used Tools & Technologies
Machine LearningRequired 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 @ 6
TensorFlow @ 6
Communication @ 4
Perl @ 6
Debugging @ 7
PyTorch @ 6
GPU @ 4
Deep Learning @ 7
AI @ 4
LangChain @ 6
- 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
Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing and the invention of the GPU. Today, NVIDIA's GPU is used for deep learning and powers systems that perceive and understand the world. NVIDIA Architecture Modeling group is expanding and seeking architects, functional modeling engineers, and simulation experts to enable functional simulation platforms across GPU generations.
Responsibilities
- Model GPU architecture, baseboard components and other features.
- Work in a matrixed environment across different modeling teams to document, design, develop tools to analyze and simulate, validate and verify models.
- Familiarize with different functional and performance simulation models across NVIDIA and work through modeling features.
- Develop tests, test plans and testing infrastructure for new architectures/features.
- Guide improvement of the simulation platform and expand resources to support future GPU architectures.
- Develop or use AI to help with day-to-day tasks.
Requirements
- BS, MS, PhD or equivalent experience in Computer Science, Electrical Engineering, Computer Engineering, or a related field with 5+ years of experience in related areas.
- Proficient programming skills in C++, C, and scripting languages such as Python or Perl.
- Solid background in Computer Architecture with experience in modeling (SystemC & TLM preferred).
- Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, and LangChain.
- Strong problem-solving and debugging skills, with a track record of driving issues to closure.
- Effective communication and interpersonal skills, with the ability to work successfully in a distributed team environment.
- Strong collaboration skills with design and engineering teams.
Compensation and Benefits
- Base salary ranges stated in the posting:
- Level 3: 152,000 USD - 241,500 USD
- Level 4: 184,000 USD - 287,500 USD
- Eligible for equity and company benefits (link provided in original posting).
Other Information
- Applications for this job will be accepted at least until February 24, 2026.
- NVIDIA uses AI tools in its recruiting processes.
- NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.