Computer Vision Research Engineer - TexkLab

TexkLab is actively seeking Computer Vision Research Interns to join our Computer Vision Team with the mission of solving real world problems using Spatial AI. Spatial AI is the capability for AI to be applied to the physical world, to tell you what an object is and where it is in 3D space in real time.

Project Areas:

Visually impaired assistance (e.g. device that helps blind people cross a street), Education (e.g. an educational game for kids), Health and fitness (e.g. a health app that tracks exercises or helps fix posture), Agriculture (e.g. plant health monitor), COVID (e.g. social distancing, mask monitoring etc), Robotics (e.g. using OAK for robot navigation / SLAM), Miscellaneous (e.g. a cool application that does not fit in any of the above tracks)

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Algorithms:

Deep learning and other computer vision methods for object detection, change detection, scene classification, event/activity recognition, 3D reconstruction from aerial imagery, video/image understanding, video/image search, and indexing, etc.

Data:

Images and videos from ground, handheld using OAK-D (is a smart camera with neural inference and depth processing capability on board capable of Spatial AI)

Infrastructure:

Opportunity to work on deep learning libraries like Caffe, PyTorch or Tensorflow; large-scale computer vision framework on the cloud.

 

Qualifications:

Education: Master’s or Ph.D. students in related fields, including computer vision, machine learning, multimedia, signal processing, imaging science, and applied mathematics.

Background: Knowledge and experience in computer vision, machine learning, deep learning (Caffe, PyTorch, Tensorflow, etc.), remote sensing or related areas.

Programming Languages: Proficiency in Python or C++.

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