The NVIDIA SoC-Clocks team is seeking an Infrastructure and Methodology Engineer dedicated to optimizing chip design, verification, and architectural workflows. This role focuses on developing automation and agentic applications to enhance overall efficiency and quality. The ideal candidate should possess proven full-stack web development and AI application development experience, along with exceptional communication skills. Preference will be given to candidates with a background in fundamental ASIC knowledge.
What You’ll Be Doing:
- Acquire comprehensive knowledge of NVIDIA’s design, verification, and architecture development environments, execution procedures, and decision-making methodologies.
- Collaborate closely with domain experts (e.g., chip design, verification, and architecture engineers) to identify process bottlenecks and formulate infrastructure improvement solutions.
- Design and implement end‑to‑end AI applications, integrating LLM‑based capabilities into web frontends, internal portals, command‑line tools, and other engineering workflows.
- Participate in the design and development of the agent application and explore excellent practices in context engineering and harness engineering. Establish rigorous evaluation benchmarks for Agent performance and optimize system to ensure reliability.
- Research advanced design and verification tool flows within NVIDIA and the wider industry and develop new applications based on these flows to address emerging challenges.
What we need to see:
- Academic background in CS, EE, CE, or AE.
- 2 years+ knowledge of ASIC principles.
- Proficiency in scripting languages such as Python, JavaScript, and Typescript. Hands-on experience using AI-native coding tools such as Claude Code, Codex, and Cursor.
- Practical experience building production AI applications. Experience with at least one LLM development framework (e.g. LangGraph, LangChain, LlamaIndex).
- Full-Stack Sensibility: While focused on AI, you understand how to integrate Agents into modern web architecture. Experience with FastAPI, React, Node.js, CI/CD, Database (MySQL/MongoDB) is preferred.
- Good judgment in decomposing engineering problems into reusable skills, workflows, and agent capabilities that can be productized for internal users.
- Fluent written and spoken English, with strong cross-team communication and consensus-building skills.
Ways to stand out from the crowd:
- Experience in building AI tools for hardware/EDA teams.
- Involvement in ASIC-related CAD projects, including SoC chip build flow, RTL design, CDC/RDC checking, static timing analysis, and simulation regression management.
- High passion for applying AI to build systems that materially improve engineering productivity in semiconductor development.
NVIDIA is recognized as one of the most desirable employers in the technology sector, with a workforce distinguished by dedication and talent. Individuals with creativity and passion for advancing cutting-edge methodologies and automation processes in complex SOC/ASIC design are encouraged to apply.