AI Research Scientist

AI Research Team @ Autodesk

As an AI Research Scientist at Autodesk Research, you will be doing fundamental and 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.

As a member of the AI Lab in Autodesk Research you will be an expert in research areas such as artificial intelligence
, deep learning
, generative AI
, machine learning
, computer vision
, reinforcement learning
, information retrieval
, and natural language processing
.

Autodesk’s AI Lab is active in the wider research community, targeting publications at CVPR, NeurIPS, ICML, ICLR, SIGGRAPH, and other top-tier conferences. We collaborate with top academic & industry labs, combining the best of an academic environment with product-guided research. We are a global team, located in London, San Francisco, Toronto, and remotely.

• Explore and develop new ML models and AI techniques
• Lead and collaborate on research projects within a global team
• Review relevant AI/ML literature to identify emerging methods, technologies, and best practices
• Work towards long-term research goals, while identifying intermediate milestones
• Build relationships and collaborate with academics and institutions
• Explore new data sources and discover techniques for best leveraging data
• Publish papers; attend and speak at conferences
• Think strategically about research directions

• 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
• Publication track record in machine learning conferences and/or journals
• Significant post-graduate research experience, or 5 or greater years of work experience (actual job title/position will be commensurate to experience)
• Good background in statistical methods for Machine Learning (e.g.
  Bayesian methods
  , HMMs
  , graphical models
  , dimension reduction
  , clustering
  , classification
  , regression techniques
  , etc.)
• Familiarity with Deep Learning techniques (e.g. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.)
• Familiarity with Py Torch ,
  Tensor Flow
  , JAX or similar frameworks
• Strong coding abilities in Python and/or C++

• Reinforcement Learning
• LLMs and Natural Language Processing
• Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry, discrete geometry, functional mapping, geometric deep learning, graph neural networks)
• Multi-modal deep learning and/or information retrieval
• Architecture, Construction, Manufacturing, Media & Entertainment or other Autodesk domains