Research Engineer, Social Presence

We aspire to achieve a vision of social presence in VR and AR where people can interact with each other across distances in a way that is indistinguishable from in-person interactions.

We are looking for research engineers who are excited about designing and implementing models that transform partial human information into realistic VR representations.

You will partner with software developers and research scientists, collaborating together on the innovation necessary to build the foundations of social presence technology.

At our lab, you will be exposed to facilities, algorithms, and data that are years ahead of anything else in existence today.

We want people who seek both the best quality and widest reach in their work.

Qualifications: Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.

Degree must be completed prior to joining Meta First author publications in computer vision, machine learning or computer graphics peer-reviewed conferences (e.g.

CVPR, ECCV, ICCV, NeurIPS, ICLR, or SIGGRAPH, etc.) Experience with realistic 3D geometry/apperance estimation/generation or motion modeling Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment Proven track record of achieving significant research results as demonstrated by grants, fellowships and/or patents Currently has or is in the process of obtaining a PhD degree in the field of computer vision, computer graphics, machine learning or a related field Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g.

GitHub) 3+ years of experience with prototyping algorithms in Python Experience with generative models such as Diffusion Models, GANs or VAEs for image and geometry generation Experience with Neural Radiance Fields, Vision Transformers or Large Language Models Responsibilities: Integrate foundation models into telepresence prototypes and live-systems Build and scale state-of-the-art algorithms and models that can transform information deficient inputs (e.g.

cameras with limited visibility, pose, text, audio) into indistinguishable-from-reality VR representations (e.g.

bodies, hair, clothes, motion, ...) Build scalable and distributed training algorithms and efficient data loading for large scale deep learning