Graduate Student Intern - Software Engineering - Austin, United States
Originally posted 2 September 2026 by the employer. Relisted by the employer on 21 September 2026.
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.
About the role
This role involves applying AI/ML techniques to geometry, mesh, and graph-structured engineering data. The work focuses on AI-driven approaches for geometry modeling, mesh generation, and topology optimization workflows.
What you'll do
- Explore and apply AI/ML techniques, including Large Language Models (LLMs), generative AI (GenAI), and Graph Neural Networks (GNNs). - 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. - Integrate AI technologies into engineering and physics-based applications, including thermal and structural simulation. - Analyze experimental results to improve the quality, robustness, and performance of AI-generated geometry and mesh models.
What you'll need
- 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.
Nice to have
- 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.
Skills: AI/ML techniques, geometry modeling, mesh generation, engineering data, simulation model preparation
This role has been open 42 days — below the 45-day median for Software Engineering Semiconductor roles.
Software Engineering Semiconductor · AI EDA Design
|
Open roles in category
107
|
Median days open
45 d
|
Median salary
$181k
|
See the full market breakdown ▾Category comparison, skills in demand, and who else is hiring
| Metric | Cadence Design Systems | All employers we track in this specialty (107 roles · 31 employers) |
|---|---|---|
| Open roles in this specialty | 7 | 107 |
| Open roles in the wider Software, Firmware & Systems family | 134 | 6142 · 145 employers |
| Median days open | 17 d | 45 d (−28 d vs this employer) |
| Median salary (USD postings) | — | $181k |
Skills observed across this category: AI/ML techniques, geometry modeling, mesh generation, engineering data, simulation model preparation
Who's hiring in this category
- Micron Technology · 15 open roles · median 38 d
- Applied Materials · 12 open roles · median 54 d
- KLA Corporation · 12 open roles · median 34 d
- Lam Research · 8 open roles · median 19 d
- Cadence Design Systems (this employer) · 7 open roles · median 17 d
- NVIDIA · 7 open roles · median 161 d
How we counted: 107 open Software Engineering Semiconductor (AI EDA Design) roles from 31 employers tracked in the SemiconductorJobs index, counted 15 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.