Applied AI Research Scientist: AEC

Job Requisition ID #

25WD85984

Applied AI Research Scientist: AEC

Position Overview

As an Applied AI Research Scientist at Autodesk Research, you will be doing applied research that will help our customers imagine, design, and make a better world.

We are a team of scientists, researchers, engineers, and designers working together on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design and construction.

This role will report to a Manager of Research Science in the AI Lab.

Responsibilities

1. Develop new ML models and AI techniques
2. Lead on research projects within a global team
3. Review relevant AI/ML literature to identify emerging methods, technologies, and best practices
4. Explore new data sources and discover techniques for best leveraging data

Minimum Qualifications

1. A Master’s or PhD in a field related to AI/ML such as: Computer Science, Mathematics, Statistics, Physics, Linguistics, Mechanical Engineering, Architecture or related disciplines
2. Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, and deploying production-ready solutions)
3. Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.)
4. Familiarity with PyTorch, TensorFlow, JAX or similar frameworks
5. Strong coding abilities in Python

Preferred Qualifications

1. Experience in the Architecture, Engineering, and/or Construction domains, including expertise with industry-specific data formats (e.g., BIM models, IFC files, AEC Contract Documents and Drawings such as Drawing Sets, Specifications, or Shop Drawings)
2. Knowledge of structured data representation and management in AEC workflows (building information modeling, structural specifications, project documentation)
3. 2D & 3D Generative AI
4. LLMs and Natural Language Processing
5. Multi-modal deep learning and/or information retrieval
6. Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry, discrete geometry, functional mapping, geometric deep learning, graph neural networks)
7. Publication track record in machine learning conferences and/or journals
8. Significant post-graduate research experience, or 5 or greater years of work experience (actual job title/position will be commensurate to experience)

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