Research Scientist Intern, 3D World Modelling, Robotics and Generative AI (PhD)

The Meta Reality Labs Research Team brings together a world-class team of researchers, developers, and engineers to create the future of AR and VR. The Surreal Vision group at RL Research is seeking exceptional Research Scientists to research and help build the egocentric machine perception functionalities and digital twins of 3D scenes that will underpin future VR and contextual-AI-enabled AR devices. The research intern will work on cutting edge research problems to innovate novel computer vision and machine learning techniques.

Collaborate with researchers to advance work across multiple research areas, including:

- Developing novel egocentric world models for action-conditioned video synthesis.
- Evaluating different egocentric input modalities (e.g., hand pose, head pose, eye gaze, body pose).
- Establish multimodal generation models including RGB video, 2D/3D flow, and depth maps.
- Curating and post-processing large-scale datasets to enable effective training.
- Investigating the impact of world models on RL algorithms for policy learning.
- Benchmarking against state-of-the-art approaches and compiling results for scientific conference submission.

Our internships are twelve (12) to twenty four (24) weeks long and we have various start dates throughout the year.Research Scientist Intern, 3D World Modelling, Robotics and Generative AI (PhD) Responsibilities

• Plan and execute cutting-edge research and development to advance the state-of-the-art in machine perception, state estimation, reconstruction and rendering of 3D objects and scenes.
• Collaborate with other researchers and engineers across machine perception teams at Meta to develop experiments, prototypes, and concepts that advance the state-of-the-art in AR/VR and AI systems.
• Work with the team to help design, setup, and run practical experiments and prototype systems related to large-scale high quality sensing and machine reasoning.
• Currently has, or is in the process of obtaining a PhD degree in the domain of computer-vision, computer graphics, 3D machine perception or machine learning
• Knowledge and hands-on experience working with 3D and projective geometry, in addition to image-space computer vision
• Hands-on experience implementing 3D computer vision algorithms as well as end-to-end training of ML models from data collection and design to evaluation
• Experience working within Python environments such as pytorch
• Experience working in a Unix environment
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment
• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, as well as first-authored publications at leading workshops or conferences such as CVPR, ECCV/ICCV, SIGGRAPH/SIGGRAPH Asia, ICLR and NeurIPS
• Strong track-record of published research in the fields of neural reconstruction, inverse rendering, neural rendering, object reconstruction and tracking, generative modelling
• Strong programming experience using python and pytorch
• Demonstrated software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
• Intent to return to a degree-program after the completion of the internship
• Experience working and communicating cross functionally in a team environment

Minimum QualificationsPreferred QualificationsAbout Meta Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.


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