Cadence Design Systems
Graduate Student Intern - Software Engineering
Cadence Design Systems is hiring a Graduate Student Intern - Software Engineering in AUSTIN 03, United States of America. Posted September 21, 2026.
Apply on Yabot Jobs
Save this job
Sign in free to get the application link, save the job, or tailor your resume to it.
Job at a glance
- Company
- Cadence Design Systems
- Location
- AUSTIN 03, United States of America
- Workplace
- On-site
- Employment
- Part-time
- Sector
- Engineering & Technology
- Posted
- September 21, 2026
About the job
At Cadence, we hire and develop leaders and innovators who want to make an impact on the world of technology.
Responsibilities
- Explore and apply AI/ML techniques, including Large Language Models (LLMs), generative AI (GenAI), and Graph Neural Networks (GNNs), to geometry, mesh, and graph-structured engineering data.
- Research and develop AI-driven approaches for geometry modeling, mesh generation, and topology optimization workflows.
- Prototype and evaluate AI-assisted methods for automating geometry creation and simulation model preparation.
- Work with researchers and engineers to integrate AI technologies into engineering and physics-based applications, including thermal and structural simulation.
- Analyze experimental results and improve the quality, robustness, and performance of AI-generated geometry and mesh models.
- Investigate methods to reduce manual modeling effort and accelerate design and simulation workflows through AI automation.
- Contribute to technical discussions, documentation, research reports, and prototype software development.
Basic Qualifications
- Currently pursuing a Master's degree or PhD in Computer Science, Engineering, Applied Mathematics, or a related field.
- Strong foundation in data structures, algorithms, and software engineering principles.
- Programming experience in C/C++ and Python.
- Familiarity with software development practices, including debugging, testing, and version control.
- Strong analytical, problem-solving, collaboration, and communication skills.
- Curiosity and enthusiasm for applying AI technologies to engineering problems.
Preferred Qualifications
- Experience with AI/ML, including deep learning, LLMs, GenAI, or GNNs.
- Familiarity with geometric modeling, mesh generation, retopology, computational geometry, or graph-based representations.
- Coursework or research experience in computer graphics, computer-aided engineering (CAE), scientific computing, or simulation.
- Exposure to CAD, CAE, EDA, or simulation-driven design applications.
- Interest in topology optimization, geometry processing, performance optimization, parallel computing, or GPU acceleration.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or similar tools.