AI Developer Intern — Interconnect Hardware Frontend, 2027

Overview

• NVIDIA's MSS-Interconnect frontend team is looking for an intern to help explore where modern AI can create real value for RTL, verification, debug, and design-review workflows.
• During your internship, you will take a focused AI-for-hardware use case from idea to working prototype, evaluate current AI tools and agents on real engineering problems, and help the team learn which capabilities are worth adopting.
• You will work alongside RTL, verification, CAD, and methodology engineers on a global, cross-site team.
• What you'll be doing: Prototype AI-assisted workflows for a focused hardware frontend problem — RTL, verification, debug, code understanding, or design review — and iterate with the engineers who use it.
• Evaluate new AI tools, models, and agent capabilities on real engineering tasks, and help assess which are worth adopting.
• Build small, reusable tools or automation that make a concrete workflow faster or more reliable.
• Partner with hardware engineers to turn a real pain point into a practical AI use case, and refine it based on usage and feedback.
• Share what works and what doesn't so the team can decide where to experiment and invest further.
• What we need to see: Currently pursuing a BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
• Solid Python and software engineering fundamentals, with some experience building automation, scripts, or tools.
• Exposure to hardware frontend workflows — RTL design, verification, debug, or design methodology — through coursework, projects, research, or prior internships.
• Enough hardware understanding to judge whether an AI-assisted solution is actually useful and technically sound.
• Strong problem-solving, communication, and a collaborative, self-driven attitude.
• Ways to stand out from the crowd: Hands-on experience building or using LLM-based tools, agents, or AI-assisted workflows — in coursework, research, or personal projects.
• Strong familiarity with modern AI tooling and good judgment on which new tools are worth trying.
• Coursework, research, or projects in frontend hardware development or debug-intensive workflows.
• Familiarity with Interconnect, NoC, Memory System, bus-fabric, or related silicon domains.