Synopsys

Job Title: Software Engineering Internship

We Are: 

Drive technology innovations that shape the way we live and connect. Our technology drives the Era of Pervasive Intelligence, where smart tech and AI are seamlessly woven into daily life. From self-driving cars and health-monitoring smartwatches to renewable energy systems that efficiently distribute clean power, Synopsys creates high-performance silicon chips that help build a healthier, safer, and more sustainable world.

Internship Experience: 

At Synopsys, interns dive into real-world projects, gaining hands-on experience while collaborating with our passionate teams worldwide—and having fun in the process! You'll have the freedom to share your ideas, unleash your creativity, and explore your interests. This is your opportunity to bring your solutions to life and work with cutting-edge technology that shapes not only the future of innovation but also your own career path. Join us and start shaping your future today!

Mission Statement: Our mission is to fuel today’s innovations and spark tomorrow’s creativity. Together, we embrace a growth mindset, empower one another, and collaborate to achieve our shared goals. Every day, we live by our values of Integrity, Excellence, Leadership, and Passion, fostering an inclusive culture where everyone can thrive—both at work and beyond.

What You’ll Be Doing:

• Collaborate with R&D teams to develop internal tools that convert complex engineering data into structured, actionable information to support analysis and decision making.
• Contribute to improving debugging and analysis workflows by identifying opportunities to automate data collection, correlation, and interpretation.
• Investigate and prototype ways to apply AI and large language models (LLMs) to assist engineers in understanding and troubleshooting technical issues.
• Validate and refine solutions using real world engineering data to ensure robustness and practical value.
• Gain hands on experience with how modern engineering organizations design and maintain scalable internal tooling used across multiple projects.

What You’ll Need:

Required

• Currently pursuing a Master’s degree in Computer Science, Electronic Engineering, or a related field.
• Hands on Python project experience, especially in: data parsing / transformation, log analysis, JSON / structured data processing.
• Familiarity with LLMs, including: prompt engineering, skills, or agent style workflows, using LLMs to analyze structured technical data.
• Comfortable working in a Linux environment.
• Strong problem-solving skills and interest in debugging complex systems. 

Nice to Have

• Background in RTL design or verification (e.g., SystemVerilog, simulation, UVM, or co-simulation concepts).
• Familiarity with EDA tools or flows (simulation, acceleration, or emulation).
• Experience with large scale log analysis or trace-based debugging.
• Coursework or projects involving HW/SW co-simulation or system level debugging.

Key Program Facts:

• Program Length: 8 Weeks
• Location: Hsinchu (X-Plan). Taiwan
• Working Model: In-office
• Full-Time/Part-Time: Full-Time preferred
• Start Date: July, 2026

Equal Opportunity Statement:

Synopsys is committed to creating an inclusive workplace and is an equal opportunity employer. We welcome all qualified applicants to apply, regardless of age, color, family or medical leave, gender identity or expression, marital status, disability, race and ethnicity, religion, sexual orientation, or any other characteristic protected by local laws. If you need assistance or a reasonable accommodation during the application process, please reach out to us.

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.

At Synopsys, we want talented people of every background to feel valued and supported to do their best work. Synopsys considers all applicants for employment without regard to race, color, religion, national origin, gender, sexual orientation, age, military veteran status, or disability.