AI Research Scientist

6 days ago

London, United Kingdom Motorsport-Total.com GmbH Full time

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.
The role will report to a Manager of Research Science in the AI Lab. Develop new ML models and AI techniques
Lead 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
Strategically direct 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. Network architectures, regularization techniques, learning techniques, loss-functions, optimization strategies, etc.)
Strong coding abilities in Python and/or C++
2D & 3D Generative AI
~ 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)
~

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