The NVIDIA SOC group is looking for ASIC verification/infrastructures and methodologies interns. In this position, you will take part in all stages to design modern complex GPU/Tegra chips with state-of-art feature and flows, you will work directly with different global teams, as Arch/SW, ASIC Design/Verification, SOCD/Clocks/SysASIC, DFT and Physical Design teams. Additionally, you will be involved in defining and creating infrastructures and methodologies that create more efficient and flexible SOCs in future.
What you’ll be doing:
- Participate in chip top integration and assembly,Engage in design/verification work of system-level units
- Optimize composing/verification flow, processes, and methodologies, Develop new tools and flows to improve efficiency and quality
- Participate in developing intelligent application systems based on Large Language Models (LLMs) for Chip Design, including conversational systems, intelligent assistants, and knowledge Q&A systems
- Learn and implement RAG (Retrieval-Augmented Generation) systems, assist in optimizing information retrieval accuracy and generation quality
- Participate in developing and testing MCP (Model Context Protocol) application integration solutions
- Develop practical application features using mainstream AI frameworks like Langchain, LlamaIndex, etc.
- Participate in model fine-tuning experiments and prompt engineering optimization
- Assist in developing AI Agent systems, learn multi-agent collaboration and workflow orchestration
- Participate in vector database integration for semantic search functionality
What we need to see:
- Pursuing a BS/MS degree from EE/CS or related majors from a prestigious university.
- Familiarity with verification methodology, tools, and flow
- Understanding of front-end ASIC design flow, including RTL design, synthesis, and timing analysis
- Proficiency in Python/Perl/JavaScript is a plus
- Proficient in English (both written and spoken) and excellent communication skills,Outstanding analytical and problem-solving skills
- Strong teamwork spirit and the ability to collaborate easily with team members
- Proficient in Python with good coding practices
- Understand basic data structures and algorithms
- Understand basic principles and applications of Large Language Models (LLMs)
- Basic knowledge of RAG, Agent, Prompt Engineering concepts
- Experience using at least one LLM API (OpenAI, Claude, etc.)
Ways to stand out from the crowd:
- AI Framework Experience**: Developed small projects or demos using Langchain, LlamaIndex, etc.
- RAG Practice**: Understand RAG principles, completed related course or personal projects
- Vector Databases**: Exposure to Milvus, ChromaDB, Faiss, Pinecone, or similar databases
- Model Fine-tuning**: Experience with fine-tuning, familiar with parameter-efficient methods like LoRA
