About this AI for Smarter IP Design Workflows role at Cadence Design Systems
At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
AI for Smarter IP Design Workflows
Location: Cadence Design Systems, Sophia Antipolis, France
Duration: 6 months
Profile: Final-year engineering student
About the Internship
Are you curious about Artificial Intelligence and interested in applying it to real engineering challenges? Do you enjoy solving problems and finding smarter ways to work? If so, we'd love to hear from you.
At Cadence, we believe great candidates come from a variety of backgrounds and experiences. You do not need to be an AI expert to apply. We are looking for motivated and curious individuals who are eager to learn and excited about exploring how AI can improve engineering workflows.
During this internship, you will work with the Memory IP R&D team to investigate how AI can improve reporting, data analysis, visualization, and automation within semiconductor design workflows. The goal is to make engineering information easier to understand, reduce repetitive tasks, and help engineers focus on innovation and problem solving.
You will be supported by experienced engineers and mentors throughout the internship and will contribute to projects that have a real impact on engineering productivity.
What You Will Do
- Explore how AI can improve IP design workflows and engineering productivity.
- Analyze engineering reports, logs, and validation results to identify opportunities for automation.
- Develop software prototypes using Python and AI technologies.
- Create clearer and more effective ways to visualize and present engineering data.
- Collaborate with engineers to understand challenges and evaluate proposed solutions.
Expected Deliverables
By the end of the internship, you will:
- Develop and demonstrate at least one AI-based prototype.
- Validate the solution on real engineering use cases.
- Document the approach, results, and recommendations.
- Present your work to the engineering team.
Success Criteria
Success will be measured by the solution's ability to provide value in one or more of the following areas:
- Reduced manual effort for report or data analysis.
- Improved visualization and accessibility of engineering information.
- Increased automation of repetitive tasks.
- Faster identification of engineering issues.
- Positive feedback from engineers using the prototype.
Preferred Qualifications
- Interest in Artificial Intelligence and emerging technologies.
- Basic programming skills (Python is a plus).
- Strong curiosity and willingness to learn.
- Problem-solving mindset and attention to detail.
- Good communication and teamwork skills.
Nice to Have
- Exposure to data analysis or software development.
- Interest in semiconductor technologies or engineering workflows.
What Matters Most
Curiosity, enthusiasm, and a desire to learn. Whether your background is in software, electronics, data science, AI, or another engineering field, we encourage you to apply.
This is an opportunity to explore how AI can transform the way engineers work while gaining hands-on experience on real-world projects used in semiconductor IP development.
