**Summary:** The Reality Labs team at Meta is seeking talented Computer Vision Engineers to join our mission to revolutionize the way people interact with information and each other through cutting-edge Augmented Reality (AR) and Mixed Reality (MR) technologies. Our goal is to make AR glasses, like our ambitious Orion project, a reality - transforming the way we live, work, and connect.We're pushing the boundaries of what's possible in AR and MR, developing innovative hardware and software products that can understand the real world and the user within their environment. By creating seamless, intuitive experiences that blur the lines between the physical and digital worlds, we aim to unlock new possibilities for people to interact, collaborate, and share moments.As part of our Reality Labs division, you'll be working alongside experts in computer vision, machine learning, and more to develop and deliver groundbreaking technologies that will power future AR glasses and other Reality Labs products. From Visual Localization, SLAM, 3D reconstruction, Context/Semantic Understanding, Mapping, Tracking, and Sensor Fusion, our team is dedicated to taking new technologies from concept to product level while iterating, prototyping, and realizing the human value they create.If you have a passion for tackling complex computer vision and machine learning challenges, love solving novel problems from first principles, or delivering state-of-the-art technologies into products used by millions of users, we want to hear from you! Are you always looking for better, faster, and more efficient solutions? Do you want to help build the core technologies that will be used 100s of Millions of users? Join us and be part of shaping the future of AR and MR, making a meaningful impact on people's lives. Apply now! **Required Skills:** Computer Vision Engineer Responsibilities: 1. Lead the design and development of 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. 2. Play a critical role in the definition and execution of long-term roadmaps in partnership and cross functional organizations in computer vision, machine learning, graphics, sensors, optics and silicon. 3. Lead and collaborate with multidisciplinary engineering and research teams to develop technologies from early exploration and incubation to production. 4. Be a go-to person to escalate the most complex online / production performance and evaluation issues that require an in depth knowledge. 5. Develop prototypes for future VR/AR/MR experiences, drive continued development, and integrate robust solutions into products. 6. Participate in cutting edge research in computer vision that can be applied to AR/VR product development. 7. Define projects for other engineers to possibly solve and achieve impact based on your direction. **Minimum Qualifications:** Minimum Qualifications: 8. Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. 9. Experience in one or more of the following areas: Deep Learning, Computer Vision, AR/VR, 3D Vision, Robotics, Machine Learning or artificial intelligence 10. Experience developing computer vision algorithms or computer vision infrastructure in C/C++ or Python **Preferred Qualifications:** Preferred Qualifications: 11. MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field. 12. Experience with distributed systems or on-device algorithm development 13. Experience in deep learning and PyTorch 14. 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 **Industry:** Internet