Facebook Reality Labs (FRL) Redmond is looking for exceptional interns to help create the next generation of virtual and augmented reality.
Our research focuses on true solutions to complex tracking problems, delivering novel technologies and algorithms fundamental to future VR and AR systems.
You’ll have the unique opportunity to work with industry-leading researchers and engineers who are defining the future of VR and AR.
Our research topics include (but are not limited to) the following areas : - Geometry guided personalization for end-to-end appearance based gaze estimation- Generative adversarial networks for view independent gaze estimation- Machine learning on 3D point clouds for shape completion / reconstruction- Semi- / self-supervised learning, domain adaptation, and other related machine learning methods for regression analysis, semantic segmentation and personalization applications- Bayesian framework for label free gaze estimation and uncertainty quantification- Machine learning / Kalman Filters for multi-modal, multi-rate sensor fusion for eye tracking- Active learning for regression analysis In particular, we welcome candidates who strive for a deep understanding of complex systems, and a strong desire to push beyond state-of-the-art.
We also welcome students with a passion for working independently in a strongly collaborative team that spans research across algorithms, hardware design and systems prototyping.
Our team at Facebook Reality Labs offers twelve (12) to sixteen (16), or twenty-four (24) weeks long internship with flexible starting dates.
Research and develop models / algorithms for gaze tracking and / or 3D shape completion / reconstruction architectures.
Collaborate with researchers and engineers across diverse disciplines.
Communication and documentation of research agenda, progress and results.
Currently has, or is in the process of obtaining, a PhD degree in Computer Science, Robotics, Applied Math, Physics or a related STEM field.
Must obtain work authorization in the country of employment at the time of hire and maintain ongoing work authorization during employment.
High levels of creativity and quick problem solving capabilities.
Interpersonal skills : cross-group and cross-culture collaboration.
Proven track record of achieving results as demonstrated in accepted papers at top computer vision and machine learning related conferences such as CVPR, ICCV, ECCV, ICLR, ICML, NeurIPS, ICPR, ICIP and / or eye-tracking conferences such as ETRA.
Record of course work on basics in Machine Learning and / or Statistical Learning theory.
At least one year experience with deep learning model development tools such as Pytorch / Tensorflow.
At least two years of experience working on topics in 3D geometry, 3D reconstruction, and / or numerical optimization OR experience in developing and training generative models such as GANs and VAEs.
Intent to return to degree-program after the completion of the internship / co-op.
Demonstrated some software engineer experience via an internship, work experience, coding competitions, or widely used contributions in open source repositories (e.g. Github).
Demonstrated experience with good software engineering practices such as code review and code documentation.