Computer Vision Engineer Full-time

The Reality Labs team at Meta is looking for Computer Vision Engineers to support our engineering teams as we build towards our goal of 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. Meta is building the Metaverse, the “spatial internet” where immersive virtual worlds will coexist with the real world. Augmented and Mixed reality will transform the way people come together to interact, work and play. By developing new hardware and software products capable of understanding the real world and the user within their environment, we aim to make it possible for people to interact with content in their environment and share it with others. Our Reality Labs division explores, develops and delivers cutting-edge technologies that serve as the foundations for the Metaverse and other future Reality Labs products, such as Oculus headsets, future AR glasses and our FB Family of Apps (Messenger, Instagram, WhatsApp). From Visual Localization, SLAM, 3D reconstruction, Context/Semantic Understanding, Mapping, Tracking, and Sensor Fusion, our team 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. Do you have a passion for exploring and solving challenging computer vision and machine learning problems? Do you love solving novel problems from first principles, or delivering SOTA technologies into products used by millions of users? Are you always on the lookout for better, faster, and more efficient solutions? Do you want to help build the core technologies that will enable the Metaverse? We encourage you to apply and join us!

Computer Vision Engineer Responsibilities

• 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.
• 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.
• Lead and collaborate with multidisciplinary engineering and research teams to develop technologies from early exploration and incubation to production.
• Be a go-to person to escalate the most complex online / production performance and evaluation issues that require an in depth knowledge.
• Develop prototypes for future VR/AR/MR experiences, drive continued development, and integrate robust solutions into products.
• 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.

Minimum Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Experience in one or more of the following areas: Deep Learning, Computer Vision, AR/VR, 3D Vision, Robotics, Machine Learning or artificial intelligence
• Experience developing computer vision algorithms or computer vision infrastructure in C/C++ or Python

Preferred Qualifications

• MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field.
• Experience with distributed systems or on-device algorithm development
• Experience in deep learning and PyTorch
• 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

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