PCB Design EDA and AI Engineer - New College Graduate 2027

• Contribute to the implementation and optimization of automation tools and processes for the hardware design for NVIDIA’s latest products.
• Participate in research and practical applications of AI in PCB design engineering.
• Support EDA research and development for the latest PCB design and manufacturing technologies.
• Communicate and collaborate closely with global EDA teams and hardware engineering teams on a daily basis.
• Work closely with PCB design, system circuit design, mechanical design, component library design, signal integrity design, system validation, and manufacturing teams to solve complex engineering automation challenges.
• Continuously optimize design methodologies and engineering workflows to improve product performance and design efficiency.

• Bachelor’s degree or above in Automation, Electrical and Electronic Engineering, Computer Engineering, or a related engineering field.
• Familiarity with electronic circuits and PCB design.
• Familiarity with Cadence or similar EDA design software.
• Background with Python or EDA scripting development experience
• Familiarity with modern software tool flows such as GitLab and CI/CD.
• Basic understanding of AI Agent practices and related concepts.
• Proficient daily English communication skills.
• Strong logical analysis and engineering problem-solving abilities.
• Honesty, resilience, and strong communication and collaboration skills, with the ability to work effectively in a cross-functional team environment.
• Self-motivated, passionate about technological innovation, and willing to continuously learn and explore new technologies.

Ways to Stand Out from the Crowd

• Experience with PCB, electronic hardware, or system design projects through coursework, competitions, research, internships, or personal projects.
• Excellent English communication skills.
• Hands-on engineering experience with AI Agents.
• Understanding of PCB manufacturing processes and design methodologies such as DFF, DFA, and DFT.
• Background of CUDA programming and the latest NVIDIA GPU architecture features, such as dedicated features of the Hopper and Blackwell architectures.