Job Requisition ID #
24WD82744 As an Intern in Autodesk Research’s AI Lab, you'll apply advanced machine learning techniques to help our customers design and create a better, safer, more sustainable world. We are a team of researchers, engineers, and industry domain experts working on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design, and construction. We are looking for an intern to work with us on machine learning research applied to design. The research involves training decoder-only transformer models on sequences encoding geometric information and evaluating the quality of the output. Candidates should have experience with transformer models, as well as a good grounding in geometry processing. We're passionate about making design tools to enable design exploration (getting to alternative design solutions), design automation (getting to the finished design faster), and sustainable design (with less negative impact). We hope to learn how our customers design today, to enable smarter software tomorrow. Autodesk's AI Lab is active in the wider research community, targeting publications at NeurIPS, ICML, ICLR, and other top-tier conferences. We collaborate with top academic & industry labs, combining the best of an academic environment with product-driven research. Responsibilities
Train decoder-only transformer models on sequences encoding CAD geometry. Write code to evaluate model performance by analyzing the generated sequences. Review literature and identify related work. Work with other researchers and engineers towards common goals. Use existing frameworks/libraries and implement necessary tools as required. Document and communicate progress. Minimum Qualifications
Full-time student pursuing an MS or Ph.D. (preferred) in Computer Science, Computational Design, Graphics, Machine Learning, or a discipline in an accredited program with at least one academic term to complete post-internship. Broad understanding of machine learning and deep learning. Excellent programming and software development skills, with experience in Python. Experience working with 2D geometry (points, vectors, and transforms). Proficient with ML & DL platforms & libraries (PyTorch, TensorFlow, Keras, scikit-learn, etc.). Proficient with training models on AWS infrastructure. Experience conducting research and publishing results. An excellent communicator and team player. Interest or experience in design (e.g., industrial or mechanical design). Preferred Qualifications
Experience working with domain-specific languages. Knowledge of computational geometry and computer graphics. Knowledge of common graph algorithms (Dijkstra, feedback arc set cycle breaking, topological sorting). Understanding of algorithms for geometric constraint solving.
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24WD82744 As an Intern in Autodesk Research’s AI Lab, you'll apply advanced machine learning techniques to help our customers design and create a better, safer, more sustainable world. We are a team of researchers, engineers, and industry domain experts working on projects that range from learning-based design systems, computer vision, graphics, robotics, human-computer interaction, sustainability, simulation, manufacturing, architectural design, and construction. We are looking for an intern to work with us on machine learning research applied to design. The research involves training decoder-only transformer models on sequences encoding geometric information and evaluating the quality of the output. Candidates should have experience with transformer models, as well as a good grounding in geometry processing. We're passionate about making design tools to enable design exploration (getting to alternative design solutions), design automation (getting to the finished design faster), and sustainable design (with less negative impact). We hope to learn how our customers design today, to enable smarter software tomorrow. Autodesk's AI Lab is active in the wider research community, targeting publications at NeurIPS, ICML, ICLR, and other top-tier conferences. We collaborate with top academic & industry labs, combining the best of an academic environment with product-driven research. Responsibilities
Train decoder-only transformer models on sequences encoding CAD geometry. Write code to evaluate model performance by analyzing the generated sequences. Review literature and identify related work. Work with other researchers and engineers towards common goals. Use existing frameworks/libraries and implement necessary tools as required. Document and communicate progress. Minimum Qualifications
Full-time student pursuing an MS or Ph.D. (preferred) in Computer Science, Computational Design, Graphics, Machine Learning, or a discipline in an accredited program with at least one academic term to complete post-internship. Broad understanding of machine learning and deep learning. Excellent programming and software development skills, with experience in Python. Experience working with 2D geometry (points, vectors, and transforms). Proficient with ML & DL platforms & libraries (PyTorch, TensorFlow, Keras, scikit-learn, etc.). Proficient with training models on AWS infrastructure. Experience conducting research and publishing results. An excellent communicator and team player. Interest or experience in design (e.g., industrial or mechanical design). Preferred Qualifications
Experience working with domain-specific languages. Knowledge of computational geometry and computer graphics. Knowledge of common graph algorithms (Dijkstra, feedback arc set cycle breaking, topological sorting). Understanding of algorithms for geometric constraint solving.
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