The AR/VR team at Facebook is helping more people around the world come together and connect through world-class Augmented, Mixed and Virtual Reality hardware and software. With global departments dedicated to AR/VR research, computer vision, haptics, social interaction, and more, we are committed to driving the state of the art forward through relentless innovation. AR and VR potential to change the world is immense-and we're just getting started.
Our Core Tech team explores, develops, and delivers new cutting-edge technologies that serve as the foundation of current and future AR/VR products. From mixed reality and human interaction to natural input and beyond, Core Tech is focused on taking new technologies from early concept to the product level while iterating, prototyping, and realizing the human value and new experiences they open up.
Computer vision and machine learning are core to creating great virtual reality technology. As a Computer Vision Engineer with the AR/VR team you'll be solving challenging problems that will help transform virtual reality from dream into reality. Specifically, we're driving advancements in eye tracking and gaze estimation, which involves work with stereo imaging, 3D geometry and image processing. We're seeking a dedicated engineer to join our team and contribute to the future of eye tracking in VR.
* Design, develop and implement new novel eye tracking and gaze estimation algorithms across all AR/VR products
Contribute to cutting edge research in computer vision that can be applied to future AR/VR products
Devise data-driven techniques to characterize the performance of eye tracking systems
Utilize multiple sensors and tracking systems to integrate eye tracking into a computer vision framework
* MSc in Computer Vision, Computer Science, Machine Learning or a related technical field
5+ years' experience working in the areas of 3D reconstruction, SLAM, machine learning, object detection and tracking and/or computer graphics
C++ coding experience
Experience working collaboratively in cross-functional teams
* PhD degree in Computer Vision, Computer Science, Machine Learning or a related technical field
Publications in top-tier journals and conferences
Experience with machine learning and deep convolutional and/or recurrent neural networks
Experience with CPU/GPU optimization
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