Snap Inc. is a camera company. We believe that reinventing the camera represents our greatest opportunity to improve the way people live and communicate. Our products empower people to express themselves, live in the moment, learn about the world, and have fun together.
We’re looking for Computer Vision Engineers with experience in 3D human reconstruction and tracking to join Team Snapchat! As a member of our 3D human reconstruction team you’ll work on creating new ways to employ computer vision and in particular human pose estimation to give Snapchatters exciting new tools and develop new human-centric Augmented Reality use cases.
What you’ll do:
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Advance the state of the art in computer vision and human pose estimation.
Develop computer vision systems to be used by millions of Snapchatters.
Learn new techniques with the full support of your peers and stay on the cutting edge.
Participate in our strong culture of mentoring.
Introduce innovations that can lead to product features or new areas of business.
Work closely with other teams to explore and prototype new product features.
Minimum Qualifications:
Masters degree or industrial experience in deep learning/computer vision
Excellent programming skills in Python and/or C++.
Experience with PyTorch and/or Tensorflow.
Strong communications and interpersonal skills.
A genuine passion for learning new things and helping colleagues improve.
Preferred Qualifications:
PhD or 5+ years of industrial experience in computer vision
Track record of delivering results in human pose estimation and/or mesh reconstruction for body/hands/face, as demonstrated by research publications (CVPR/ICCV/ECCV/NeurIPS) and/or work on human pose-related products.
Track record of delivering results on 3D scene reconstruction, point cloud processing and RGB-D fusion, as demonstrated by research publications (CVPR/ICCV/ECCV/NeurIPS) and/or work on 3D geometry-related products.
Hands-on experience with mobile inference and C++ programming.
Experience working with 3D meshes and knowledge of 3D tools.