Explore how large language models (LLMs) and intelligent multi-agent systems can enable advanced reasoning in architecture, engineering, and construction (AEC)
Help design AI systems that reason over complex, multimodal design problems — integrating spatial, quantitative, textual, and procedural knowledge
Develop and execute a research agenda focused on advancing AI reasoning and multimodal learning in architecture, engineering, and construction (AEC)
Create and refine cutting-edge algorithms, drawing from multiple approaches in artificial intelligence
Collaborate with researchers and engineers across diverse disciplines, including communicating research plans, progress, and results
Explore methods for structured reasoning and collaborative problem-solving among intelligent systems
Shape the future of Autodesk's architecture, engineering, and construction products through published research and practical applications

Full-time student pursuing an MS or PhD (preferred) in Computer Science, Artificial Intelligence, Computational Design, Applied Mathematics, or a related field
Broad understanding of machine learning, deep learning, and reasoning systems
Strong programming skills in Python, with proficiency in PyTorch or TensorFlow
Demonstrated experience in conducting, analyzing, and communicating research
Excellent written and verbal communication skills, and ability to collaborate in cross-disciplinary teams
Expertise in an area such as natural language processing, computer vision, 2D/3D geometry representation learning, reinforcement learning, graph neural networks, unsupervised/self-supervised learning, meta-learning, and/or generative models.
Distinguished research achievements, such as intellectual property filings, awards, and leading authorship in top-tier venues (including but not limited to major ML/AI conferences, workshops, and journals)
Demonstrated programming experience through professional roles, internships, hackathons, or contributions to open-source repositories (e.g., GitHub)
Experience wrangling large, complex, high-dimensional data for large-scale training.
Proven ability to tackle complex challenges independently
Passion for bridging AI reasoning with real-world AEC design and simulation workflows.

Intern, AI Research

Key skills