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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