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 diversity of human appearance and applying that model to the process of rapidly generating new avatars. This role is primarily centered on the generation of our codec avatars from images or videos captured in real-world scenarios. This involves training large-scale universal prior models using over a billion images and videos, and then applying these models to any new image or video to swiftly generate realistic 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 machine learning training 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 digitizing every individual globally using a single image or video.

Codec Avatars Research Engineer Responsibilities

• Develop a large-scale machine learning model to build a universal prior for human features such as face, body, hands, hair, etc.


• Personalize the universal prior model on a single human image/video to rapidly construct a realistic codec avatar.


• Define data requirements and collaborate with the Research SuperCluster team to efficiently load data.


• Partner with the GenAI team to explore and implement various state-of-the-art models and methods, including transformers, diffusion models, hypernetworks, etc.


• Collaborate with the Universal Encoder team to support the real-time driving of the generated codec avatar.


• Define, design, and implement automatic pipeline of avatar generation from images/videos.

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.


• Masters or higher degree in Computer Science or a related technical field, or equivalent experience.


• Experience with multi-node machine learning training workflows and frameworks.


• Experience in developing or applying computer graphics algorithms.


• Experience in developing or applying computer vision algorithms.


• Adept communication skills, including experience in driving decision-making processes.


• Experience working with cross-functional teams including, research, software, legal, privacy, and security.


• Proficiency in Python.


• Experience in Linux/shell scripting development.

Preferred Qualifications

• PhD degree in Computer Science or a related technical field, or equivalent experience.


• 5+ years of experience in a related industry.


• Publish papers on CVPR, ECCV, ICCV, T-PAMI, SIGGRAPH, SIGGRAPH Asia, etc. as the first author


• Understanding of deep neural network training, experience with large-scale models, diffusion models, hypernetworks, etc.


• Proficiency in C++.

Start preparing
Learn about how to prepare for your interview with our interview guide, tips, and interactive experiences.
Visit interview prep