Senior GPU Functional Modeling Architect

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +1 · Remote

This role involves modeling GPU architecture and components, developing tools for simulation and analysis, and creating test infrastructure for new architectures. While the role mentions using AI for day-to-day tasks and proficiency in ML frameworks, its core focus is on the engineering and simulation of GPU hardware, not directly shipping AI models or agents.

What you'd actually do

  1. Modeling of GPU architecture, baseboard components and other features
  2. Work in a matrixed environment, across the different modeling teams, to document, design, develop tools to analyze and simulate, validate and verify models
  3. Familiarize with different functional and performance simulation models across Nvidia and work through modeling features
  4. Develop tests, test plans and testing infrastructure for new architectures/ features
  5. Guide the improvement of the simulation platform and expand other resources to support future GPU architectures

Skills

Required

  • 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 (System C & TLM preferred)
  • Proficiency in Python and ML frameworks like 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

What the JD emphasized

  • Proficient programming skills in C++, C, and scripting languages such as Python or Perl.
  • Solid background in Computer Architecture with experience in modeling (System C & TLM preferred)
  • Proficiency in Python and ML frameworks like PyTorch, TensorFlow, and LangChain

Other signals

  • GPU architecture modeling
  • functional simulation platforms
  • develop tools to analyze and simulate
  • Develop tests, test plans and testing infrastructure
  • Develop or use AI to help with day-to-day tasks