Computer Vision Engineer

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 upscale 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.

• 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

• 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 Py Torch
• 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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