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The Facebook Reality Labs (FRL) organisation 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, FRL 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.Our Mixed Reality (XR) organization in Zurich is focused on cutting edge research and development of machine perception technologies from early concepts to production level across all of Facebook’s AR/VR products and surfaces. These include Oculus products, Facebook Glasses 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, Spatial , Calibration and more.In this role, you will be researching and applying a range of software, computer vision and machine learning techniques for solving challenges that bridge virtual and real worlds and will impact billions of people. We're addressing a variety of technical challenges in the areas of real-time image processing, 3D graphics, SLAM, scene reconstruction, machine perception, visualisation and human interaction. As well there are opportunities to collaborate with researchers in Facebook Reality Labs (FRL) and Facebook AI Research (FAIR).
Computer Vision Engineer Responsibilities:
Computer Vision Engineer Responsibilities:
- Design and develop novel computer vision and/or machine learning algorithms in areas such as: real-time scene and object tracking, reconstruction and understanding as well 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 VR/AR/MR experiences, drive continued development, and integrate robust solutions into product.
- Collaborate with cross-functional engineering and research teams from Facebook Reality Labs (FRL) and Facebook AI Research (FAIR)in computer vision, machine learning, and graphics.
- Participate in cutting edge research in computer vision that can be applied to AR/VR product development.
- Define projects for other engineers to possibly solve and achieve impact based on your direction
- BSc degree in Computer Science, Computer Vision, Machine Learning, or related technical field.
- 3+ years of experience developing and designing Computer Vision and/or Machine Learning technologies and systems.
- 3+ years of experience engineering in C++ and/or Python
- Prototyping and engineering experience in at least ONE relevant specialization area in either Computer Vision or Machine Learning: SLAM State Estimation Sensor Fusion Generative models such as GANs Pose estimation: Body, Facial, Hand or Eye Tracking Dense 3D reconstruction Object detection, segmentation and tracking Scene understanding/ Semantic Segmentation Photorealistic rendering Factory, HW, Camera or Online Calibration
- MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field.
- 2+ years of industry experience working on projects such as: real-time SLAM and 3D reconstruction, sensor fusion and active depth sensing, object and body tracking and pose estimation, and/or image processing. Image and/or semantic segmentation, 2D and 3D key point estimation and surface reconstruction, depth estimation, generative methods such as GANs, or photorealistic rendering.
- Developing and designing Computer Vision and/or Machine Learning technologies and systems for running on edge devices (mobile phones, and/or custom hardware)
- Background in machine learning with experience in large scale training and evaluation of deep convolutional and/or recurrent neural networks and/or GANs.
- Publication track record at conferences such as SIGGRAPH, CVPR, NIPS, ECCV, ICCV, ISMAR, ICML, etc.
- Applications and resumes to be submitted in English.