Reality Labs (RL) teams are looking for exceptional interns to help us create next generation interaction technologies for virtual and augmented reality. Join a full-stack team working on computer vision, machine learning, geometric and appearance modeling, physically-based modeling, sensor design and fusion, and human computer interaction. We are accepting applications from those interested in (but not limited to) the following areas:*Tracking of hands, bodies and objects and their interactions through machine learning, computer vision and sensor fusion*Egocentric human action recognition and emotion recognition*Hand motion sequence modeling for hand-object interaction using deep generative models or physical simulation*Representation modeling (e.g., implicit, appearance, geometry) of hands, bodies and objects for fast simulation and tracking*Efficient deep learning (e.g., neural architecture search, sparsity, quantized networks)*Interaction design for hands, bodies and objects in virtual reality and augmented reality*Sensor fusion (e.g. of pressure, RF, EXG, IMU) with optical tracking*Efficient and generalizable detectors for predicting keypoints, segmentations, normals, and depth*Accurate and efficient 3D representations of deformable shapes such as clothing and hair

Research Scientist Intern, Machine Perception for Input and Interaction (PhD) Responsibilities:

• Design and execution of algorithms in the domain of computer vision, machine learning, computer graphics, sensor fusion, or HCI software and hardware prototyping
• Design of user studies and experiments
• Collaboration with other researchers across various disciplines
• Communication of research agenda, progress, and results

Minimum Qualifications:

• Currently has, or is in the process of obtaining, a PhD degree in EE/CS, Applied Math or a related STEM field
• Experience in one or more of the following: computer vision (e.g. tracking, pose estimation, action/emotion recognition), computer graphics (e.g. appearance, geometry, physically-based modeling), robotics (state estimation, optimal control), machine learning (e.g. efficient deep learning, domain adaptation, transfer learning), natural language processing, or human-computer interaction
• Excellent communication skills
• High levels of creativity and problem solving capabilities
• Experience with C++ or Python
• Experience with ML frameworks such as PyTorch, Tensorflow, etc.
• Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment

Preferred Qualifications:

• Proven track record of achieving significant results as demonstrated by grants, fellowships, patents, or first-authored publications at leading journals or conferences such as CVPR, ECCV/ICCV, BMVC, NeurIPS, ICML, ICLR, CHI, SIGGRAPH/SIGGRAPH Asia, ICRA, IROS, RSS, TPAMI, IJCV, etc.
• Demonstrated software engineering experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. GitHub)
• Experiences working on high volume multi-sensor streaming data processing and real-time multi-sensor, in particular cameras, fusion for computer vision and machine learning systems
• Experiences on optimizing and deploying deep learning models on SoC of mobile devices for high performance real time applications
• Experience with Machine Learning for 3D data (such as meshes, point clouds, gaussian splatting, and voxels)
• Experience with Machine Learning for Visual Synthesis

About 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.