AI Research Scientist - Computer Vision & GenAI

The Reality Labs organization at Meta is helping more people around the world come together and connect through world-class Augmented and Virtual reality (AR/VR) products. With global departments dedicated to research and development, AR/VR is committed to driving the state of the art forward through relentless innovation. The potential to change the world is immense - and we're just getting started.Individuals in this role are expected to be recognized experts in Artificial Intelligence and Machine Learning, particularly in areas such as DL, Computer Vision, Affective Computing, Behaviour Understanding, and Generative AI. As a Research Scientist, you will help us develop models, algorithms, datasets, and evaluation methodologies for the generation and animation of avatars to facilitate new and engaging user experiences, and apply them to large-scale production that has the potential to reach billions of users.

AI Research Scientist - Computer Vision & GenAI Responsibilities:

• Help to develop the next generation of GenAI models for avatar creation and animation
• Harness passion for technology and propose new research roadmaps which can lead to the creation of new models that can be applied to multiple applications
• Employ knowledge in the following areas: multi-modal data processing, affective computing, generative AI, and neural rendering
• Work towards long-term ambitious research goals, while identifying intermediate milestones
• Disseminate findings of research by publishing papers in high impact conferences and journals

• PhD degree in Computer Science, Computer Engineering, Computer Graphics, Applied Sciences, Mathematics, Physics, or related field
• Experience in Python and PyTorch
• Track record of publishing papers in high-quality journals and conferences such as CVPR, ECCV/ICCV, SIGGRAPH, NIPS

• Experiences in the creation and processing of large audio-visual datasets
• Experience with generative AI / neural rendering models
• Experience in solving complex problems and comparing alternative solutions, trade-offs, and different perspectives to determine a path forward
• Experience with affective computing and behaviour understanding