PCB Design EDA and AI Engineer - New College Graduate 2027
At a glance
Mid-level AI Engineering role at NVIDIA. Taiwan, Taipei · full-time.
Pay not stated AI Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build and refine automation tools and processes used in hardware design for current products
- Explore practical uses of AI in PCB engineering and contribute to EDA development for newer PCB design and manufacturing methods
- Coordinate daily with global EDA and hardware groups, plus teams spanning PCB, circuits, mechanical design, validation and manufacturing
- Improve design practices and engineering workflows to raise product performance and design efficiency
What you bring
- You hold at least a bachelor’s degree in automation, electrical and electronic engineering, computer engineering or another related engineering field
- You understand electronic circuits and PCB design, and have used Cadence or comparable EDA software
- You have Python experience or have developed EDA scripts, and understand software workflows such as GitLab and CI/CD
- You grasp basic AI Agent concepts and can communicate effectively in English for daily work
Who this fits
This is an entry-level opportunity for a new college graduate, with structured training, mentorship and practical project work. You’ll suit work that combines PCB design, EDA and AI with close collaboration across engineering teams.
From the employer
NVIDIA is at the forefront of the AI revolution, building the computing platforms that power the world’s most advanced AI systems. From GPUs and AI servers to high-speed networking infrastructure, we continue to push the boundaries of computing technology. As part of the PCB design team, you will work with industry-leading engineers and contribute to the automation implementation of hardware design for next-generation AI accelerated computing platforms.
Through structured training, mentorship, and hands-on project experience, you will grow into a hardware EDA and AI design expert with a system-level perspective and help shape the future of computing architecture.
What You’ll Be Doing:
- 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.
What We Need to See:
- 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.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.