Computer Vision engineer


Job Description


  • Develop and test convolutional neural network (CNN) architectures for depth estimation and lightfield image processing.
  • Deploy CNN on mobile and achieve real-time performance.
  • Stay on top of technological advances in deep learning and lightfield imaging.


Requirements ● PhD or MS in computer vision or machine learning, or equivalent experience. ● Experience building deep learning architectures for commercial products. ● Proficiency in Python (particularly, numpy, scipy, pandas, scikit-image, and scikit-learn) and C/C++. ● A good understanding of the fundamentals and best practices of deep learning. ● Experience with tools such as Caffe, Torch, Theano or TensorFlow. ● Experience with open source vision packages such as PCL and OpenCV. ● Experience with data cleaning, analysis, and developing efficient, accurate data annotation schemes. ● Experience with commercial software development processes: good software hygiene regarding code documentation, unit testing, bug tracking, and version control. ● Familiarity with state-of-the-art CNN architectures such as ResNet, VGG, GoogleNet (Inception), Faster RCNN, and Mask R-CNN. ● Highly motivated, team player with strong technical collaboration skills and desire to learn quickly and develop new skills. ● The desire to be part of a fast-moving start-up and work in a collaborative environment with few rigid boundaries. ● GPU programming experience is a plus. ● Experience with OpenCV ● Experience building and configuring Android OS flavors


1.5M ~ 2.4M TWD/year



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台北市松山區南京東路四段2號3樓 Taiwan Tech Arena

About us

We save device makers the money and space typically consumed by depth sensors by allowing them to generate 3D and depth by using dual cameras paired with our AI-based software solution, thereby increasing camera and device capabilities for consumer benefit.

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Jeff Tsai

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