We are looking for ASIC Design Interns! NVIDIA MMPLEX team is based in Shanghai with more than 300 team members. We deliver cutting-edge IP solutions across NVIDIA product lines including datacenter, GeForce, Automotive, and Networking. Our IPs include micro-processors, security, DL/CV accelerators, display, video encoder/decoder, and image processing.

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In this internship, you’ll work closely with senior engineers on design methodology and workflow efficiency, including building AI-assisted automation/agents to improve how we design, verify, and debug hardware IP. Join us if you want to learn world-leading IP development practices and help modernize engineering workflows.

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What you’ll be doing:

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• Design methodology development: improve existing RTL/design/verification workflows with automation and best practices
• Build AI agents/tools to accelerate engineering tasks
• Collaborate with senior engineers to improve PPA via better flows, debugging efficiency, and quality gates
• Prototype and deploy scripts/services that integrate with existing toolchains

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What we need to see:

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• Pursuing a Master’s degree in EE/CS or related field
• Solid fundamentals in digital design and Verilog/SystemVerilog
• Basic C/C++ programming skills
• Hands-on experience using existing AI/LLM models to accomplish engineering tasks
• Familiarity with prompting and evaluating model outputs (accuracy, hallucination handling, reproducibility)
• Fluent English with good communication and documentation skills

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Ways to stand out from the crowd:

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• Prior experience building AI agents (tool-using agents, RAG, workflow automation) for technical tasks
• Experience with prompt engineering, prompt tuning/iteration, and creating reusable prompt templates/playbooks
• Python proficiency (plus Shell/Makefile/Perl) and comfort integrating with real engineering workflows
• Familiar with ASIC design/verification process and tools (lint, CDC/RDC, synthesis, simulation/regression)
• Strong ownership: can take an ambiguous workflow problem and turn it into a measurable efficiency/quality improvement

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