Intern, AI Lab

Autodesk · Competitive · London
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As a 2022 Summer Intern at Autodesk Research youll 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. Were 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.

Autodesks 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.


  • Design and implement deep learning algorithms & prototypes
  • Improve existing algorithms by implementing new features
  • Communicate ideas, problems, and results with the team
  • Collaborate with researchers and developers in the team
  • Co-publish with Autodesk AI Lab collaborators
  • Read papers and perform literature reviews
  • Evaluate existing algorithms and reproduce results on specific datasets
  • 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
  • Proficient with ML & DL platforms & libraries (PyTorch, TensorFlow, Keras, scikit-learn, etc.)
  • 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

  • Deep expertise in an area such as computer vision, 2D/3D geometry representation learning, reinforcement learning, graph neural networks, unsupervised/self-supervised learning, meta-learning, and/or generative models.
  • Knowledge of 3D computer graphics, computational geometry, and 3D geometry manipulation
  • Experience with CAD

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