Silicon Validation Engineer (RDSS Intern)

Job Title

Silicon Validation Engineer (RDSS Intern)

Role Summary

Join the Silicon Co-Design Group to validate pre-production NVIDIA silicon. You will work in the lab on real chips from early bring-up through production sign-off, building characterization methods, debugging failures, and producing data that informs future designs.

Experience Level

Entry-level internship for new graduates; intended for participants in the 2027 RDSS program. This role expects hands-on lab and engineering work rather than prior long-term industry experience.

Responsibilities

Deliver hands-on silicon validation, characterization, and automation to close the simulation-to-silicon gap and enable production-quality chips.

• Characterize pre-production silicon: speed, performance, power, yield, and quality from bring-up to production sign-off.
• Evaluate silicon features against real-world workloads and quantify benefits and costs for future architectures.
• Develop scalable characterization and validation methodologies that correlate measured behavior to design.
• Lead failure analysis: form hypotheses, design experiments, and trace root causes across circuit, firmware, and software.
• Analyze real-world workloads (LLM inference/training, generative AI, AAA games, autonomous stacks) to optimize performance and energy efficiency.
• Build and deploy AI-driven analysis flows, data pipelines, and automated triage tools to reduce cycle time.
• Develop automation and tools for characterization, data collection, test execution, and analysis used by the team.

Requirements

Concise list of must-have technical skills and traits; separate section below covers formal education.

Must-have:

• Solid fundamentals in digital design, computer architecture, circuit analysis, signal integrity, and statistics (applicable under pressure).
• Proficiency in Python, C/C++, or equivalent and experience building tools or automation.
• Demonstrated ownership of outcomes and problem-solving under ambiguity.

Nice-to-have:

• Experience building AI/LLM-based solutions or agentic workflows for engineering problems.
• Experience developing methodologies or frameworks adopted by other teams.
• Lab experience with oscilloscopes, logic analyzers, BERTs, or similar equipment.

Education Requirements

BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or Systems Engineering.

About the Company

Company: NVIDIA

Headquarters: Santa Clara, California, USA

NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.