Reality Labs (RL) teams are looking for exceptional interns to help us create the next generation of human-centric interaction technologies for wearables, virtual and augmented reality. Join a full-stack team working on machine learning, generative modeling, multimodal-models from a high diversity of sensor types. We are accepting applications from those interested in (but not limited to) the following areas:
- Tracking of bodies, faces and hands and their interactions through machine learning, computer vision and sensor fusion
- Egocentric human action recognition and emotion recognition
- Generative models for human motion and interactions from diverse sensors and conditioning signals
- 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 for human centric use cases
- Efficient and generalizable detectors for predicting keypoints, segmentations, normals, and depth
- Accurate and efficient 3D representations of deformable shapes such as clothing and hair
Our internships are twelve (12) to twenty four (24) weeks long and we have various start dates throughout the year.
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
- Contribute to academic research submission
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
- Experience with Human centric machine learning tasks
- Intent to return to degree program after the completion of the internship/co-op
- Experience working and communicating cross functionally in a team environment
