Meta Reality Lab’s Codec Avatar Research team is building technology to enable immersive, photorealistic social presence. Codec Avatars are real-time live-drivable representations that match the appearance of their users. As part of the Lab’s Instant Codec Avatar group, you’ll work to scale up Codec Avatar technology by modeling the manifold of human motion and applying that model to the process of motion and behavior synthesis. This role is primarily centered on the animation of our codec avatars from multimodal inputs such as audio, image, and text. This involves training large-scale universal prior models using large-scale 2D and 3D datasets, and then applying these models to downstream tasks focusing on agentic Codec Avatars. As part of this role, you will collaborate with a team of research scientists, research engineers, and software engineers to pioneer research in the field of digital humans. You will work with some of the largest 3D motion datasets in the world, supported by an advanced cluster of thousands of GPUs. You will be responsible for designing and conducting research experiments, contributing significantly to our mission of building fully autonomous avatars.
Locations
Pittsburgh, PA, US
Burlingame, CA, US
Salary
Salary not disclosed
Skills Required
Pythonintermediate
Linux/shell scriptingintermediate
Multi-node machine learning training workflowsintermediate
Computer graphics algorithmsintermediate
Computer vision algorithmsintermediate
Required Qualifications
Bachelor's degree in Computer Science, Computer Engineering, or relevant technical field (degree)
Master's or higher degree in Computer Science or related technical field (degree)
Experience with multi-node machine learning training workflows and frameworks (experience)
Experience in developing or applying computer graphics algorithms (experience)
Experience in developing or applying computer vision algorithms (experience)
5+ years experience in machine learning and modeling of 3D humans (experience)
PhD degree in Computer Science or related technical field (degree)
Responsibilities
Develop a large-scale machine learning model to build a universal prior for human motion and behavior
Define data requirements and collaborate with the Research SuperCluster team to efficiently load data
Explore and implement various state-of-the-art models and methods, including transformers, diffusion models, and multimodal LLMs
Collaborate to support the real-time animation of the avatars
Define, design, and implement automatic pipeline to leverage large amounts of 2D video data to enhance 3D motion generation
Benefits
bonus: Bonus included in compensation
equity: Equity included in compensation
general: Additional benefits offered by Meta (details available on Meta's benefits page)