Computer Vision & Machine Learning Engineer PhD or Postdoc Grad

Oculus Rift

Zürich - vor 4 Tagen

neuvoo.com
Stellenbeschreibung

The AR/VR organization at Facebook is helping more people around the world come together and connect through world-class Augmented and Virtual reality (AR/VR) products. With global departments dedicated to research and development in computer vision, machine learning, haptics, social interaction, and more, AR/VR is committed to driving the state of the art forward through relentless innovation. The potential to change the world is immense - and we’re just getting started.Augmented and Virtual reality will transform the way people come together to work and play. By developing new hardware and software products capable of understanding human appearance, movement and expression, we aim to make it possible for people to feel like they are directly in front of each other, despite being separated by vast distances. Our XR People organization in Zurich is focused on research and development of machine perception technologies from early concepts to production level across all of Facebook’s AR/VR products and surfaces including Oculus products and Family of Apps (Facebook, Instagram, Messenger, WhatsApp). We develop core capabilities across a range of product domains including Avatars, AR/VR remote presence / calling, AR Commerce, AR Sharing, and more. In this role, you will be researching and developing state of the art computer vision and machine learning technologies for solving challenges that bridge virtual and real worlds and can impact billions of people. You will be setting technical direction for the projects you work on and will have opportunities to collaborate with researchers in Facebook Reality Labs (FRL) and Facebook AI Research (FAIR). There are lots of exciting and challenging unsolved problems in computer vision and machine learning for AR/VR. It is early days and we're looking for you to usher in the next era of human - human and human - computer interaction by solving these problems together with us.

Responsibilities

Design and develop novel computer vision and machine learning algorithms in areas such as segmentation, face tracking, body tracking, key point estimation, depth sensing, generative approaches such as GANs, 3D stereo and volumetric reconstruction, avatars, reconstructions and virtual try-ons. Develop prototypes for future AR/VR experiences, drive continued development, and integrate robust solutions into product. Collaborate with cross-functional engineering and research teams in computer vision, machine learning, and graphics. Participate in cutting edge research in computer vision that can be applied to AR/VR product development.

Minimum Qualifications

PhD degree in Computer Science, Computer Vision, Machine Learning, or related technical field. 2+ years of experience engineering in C++ or Python gained during university research projects 2+ years of university research experience developing and designing Computer Vision or Machine Learning technologies and systems for running on edge devices (mobile phones, and/or custom hardware). University Research experience on prototyping and engineering in at least ONE relevant specialization area in Computer Vision or Machine Learning: Generative models such as GANs / Pose estimation and dense 3D reconstruction / Object detection, segmentation and tracking / Scene understanding / Photorealistic rendering.

Preferred Qualifications

PhD or Postdoc degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field. 2+ years of industry or university experience working on projects in areas such as: object detection, segmentation, tracking, 2D and 3D key point estimation and surface reconstruction, depth estimation, generative methods such as GANs, photorealistic rendering. Background in machine learning with experience in large scale training and evaluation of deep neural networks (convolutional, recurrent, GANs). Experience with CPU/GPU and mobile optimization. Publication track record at conferences such as SIGGRAPH, CVPR, NIPS, ECCV, ICCV, ISMAR, ICML, etc.
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