Intern, Research Engineer - Geometry Generation

Intern In Autodesk Research

As an Intern in Autodesk Research, you will conduct research on foundational models and 3D CAD design software. Our team combines expertise in machine learning, 3D B-rep generation, geometry processing, and computer graphics to develop neural CAD—a category of generative AI foundation models designed to directly reason about CAD objects. Moving far beyond simply incorporating large language models into existing solutions, Autodesk has completely reimagined the traditional software engines that create CAD geometry. This new category of generative AI foundation models offers a path to the future of connected Design and Make processes. This project focuses on developing methods for generating real-world CAD workflows using large datasets.

Responsibilities

• Perform literature reviews, implement solutions, communicate progress with stakeholders, and write reports for the project
• Process Boundary representation geometry and render images for dataset creation
• Adapt state-of-the-art methods to the CAD space for 3D geometry generation and real-world applications in Fusion software

Minimum Qualifications

• Strong interest in 3D generation and solving real-world challenges
• Passion to learn and push the frontier of foundation models applied to CAD, one of the most challenging data types
• Knowledge of computer graphics and geometry processing
• Proficiency in programming languages such as C++ and Python
• Broad understanding of machine learning and deep learning
• Full-time student pursuing an MS or PhD in Computer Science, Artificial Intelligence, Computational Design and Fabrication, Applied Mathematics, Engineering, or a related field

Preferred Qualifications

• Expertise in areas such as vision-language models/large language models and 3D generation
• Publication records on topics relevant to the group
• Experience in CAD design engineering
• Experience with Ray, AWS, and distributed training frameworks

Salary is one part of Autodesk's competitive compensation package. Offers are based on the candidate's experience, educational level, and geographic location.