Graduate Student Intern Software Engineering

Cadence; Austin (TX); On-site; USD 39,000 - 55,000; Full time

Job summary

Cadence in Austin is seeking a graduate student to apply AI/ML techniques to geometry, mesh, and graph-structured data, advancing engineering simulations and workflows.

You will prototype AI-assisted methods for geometry creation and simulation setup, collaborating with researchers to integrate AI into physics-based applications and improve model quality and performance.

Qualifications

• Pursuing a Master’s degree or PhD in CS, Engineering, Applied Math, or related field.
• Strong foundation in data structures and algorithms.
• Experience with C/C++ and Python.
• Familiar with debugging, testing, and version control.
• Excellent analytical, problem-solving, and communication skills.
• Curiosity about applying AI to engineering problems.

Responsibilities

• Explore and apply AI/ML techniques to geometry, mesh, and graph data.
• Research AI-driven geometry modeling, mesh generation, and topology optimization.
• Prototype AI-assisted methods for automating geometry creation and simulations.
• Collaborate with researchers to integrate AI into engineering and physics-based apps.
• Analyze results and improve AI-generated geometry and mesh models.
• Investigate reducing manual modeling to accelerate design workflows.
• Contribute to technical discussions, docs, reports, and prototype software.

Skills

C/C++

Python

Algorithms

Data Structures

Software Engineering

Debugging

Version Control

Collaboration

Communication

AI/ML familiarity

Education

Master's or PhD (CS/Engineering/Applied Math)

Job description

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.