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NVIDIA

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SOC Design Team Methodology Intern - 2027

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Summary

An intern on NVIDIA's SOC Design Methodology team in Shanghai will analyze and improve digital ASIC front-end design flows, then build AI agents and automation scripts (Python/Perl, LLM-based tooling) to speed up and automate chip design work used across NVIDIA's SOC projects.

The NVIDIA System-on-Chip (SOC) design group is looking for a motivated intern to join our Methodology team. In this role, you will help improve the way we design, configure, and verify in SOC Design fields— making them faster, more reliable, and increasingly AI-assisted. This is a hands-on opportunity to work at the intersection of digital ASIC front-end methodology and applied AI. You will contribute to real production flows used across NVIDIA's SOC projects, partner with experienced engineers, and see how modern AI agents can accelerate chip design. We are looking for someone who is curious about finding problems, open-minded in solving them, quick to learn new tools, and detail-oriented in execution — while being organized, collaborative, and a strong communicator.

What You'll Be Doing:

  • Get up to speed on NVIDIA's SOC project development environment, tooling, and design flows.

  • Identify pain points in SOC configuration work and related methodology areas, and help scope opportunities for improvement.

  • Review conventional SOC design flows, document bottlenecks, and propose and prototype upgrades that improve turnaround time, quality, or automation.

  • Develop and refine AI agents and automation scripts to support "Speed of Light" execution — helping engineers move faster by reducing manual, repetitive steps.

  • Contribute to documentation, runbooks, and best-practice guides so that methodology improvements are repeatable and adoptable by the broader team.

  • Collaborate with SOC Design engineers to gather requirements, validate ideas, and iterate on solutions.

What We Need to See:

  • Currently pursuing a MS (or higher) Students in Electrical Engineering, Computer Science, who will graduate at 2028

  • Working knowledge of digital ASIC front-end design flows

  • Strong scripting skills — Python, Perl, or similar languages — with the ability to automate tasks and build maintainable tooling.

  • Genuine interest and foundational knowledge in AI agent development (e.g., LLM-based agents, prompt design, tool-use / function-calling, or agentic workflows).

  • Fluent English, both written and spoken, for effective collaboration in a global team.

Ways to Stand Out from the Crowd:

  • Coursework, projects, or internships in SOC design methodology.

  • Hands-on experience building or integrating AI agents (e.g., LangChain, LlamaIndex, OpenAI-style tool use, or similar frameworks).

  • Familiarity with version control (Git), CI/CD, and software engineering best practices.

  • Comfort working in a Linux development environment with large codebases and EDA toolchains.

  • A problem-finding mindset — you don't just solve assigned tasks, you proactively surface issues and propose improvements.

  • Strong communication and teamwork, with the ability to explain technical trade-offs clearly to both engineers and stakeholders.

What they ask for

Required

  • Currently pursuing an MS (or higher) in Electrical Engineering or Computer Science, graduating in 2028
  • Working knowledge of digital ASIC front-end design flows
  • Strong scripting skills in Python, Perl, or similar languages, with ability to automate tasks and build maintainable tooling
  • Genuine interest and foundational knowledge in AI agent development (LLM-based agents, prompt design, tool-use/function-calling, agentic workflows)
  • Fluent English, both written and spoken

Preferred

  • Coursework, projects, or internships in SOC design methodology
  • Hands-on experience building or integrating AI agents (e.g., LangChain, LlamaIndex, OpenAI-style tool use)
  • Familiarity with version control (Git), CI/CD, and software engineering best practices
  • Comfort working in a Linux development environment with large codebases and EDA toolchains
  • Problem-finding mindset — proactively surfacing issues and proposing improvements
  • Strong communication and teamwork, able to explain technical trade-offs clearly

Skills

See also

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