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Computer Vision Engineer

輝翠TECH株式会社

  • CUDA
  • Python
  • C++
  • Deep Learning
  • TensorFlow
  • Computer Vision
  • Embedded systems
  • semantic segmentation
  • YOLO
  • neural network architectures

For the creation of a custom model for AI technology, the identification of possible terrain for anomalies and walking, various types of classification algorithms for diseases and pests, and the development of time series analysis, extensive work is required. The ability to develop applications and tools in Python and/or C++, and technical communication skills in English are essential.

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Image Processing Software Engineer

株式会社フィックスターズ

  • GPU
  • CUDA C/C++
  • CNN
  • Git
  • AI
  • GitHub
  • Linux
  • Machine Learning
  • C++
  • PyTorch

In the position of image processing software engineer, we are developing image processing, machine learning/deep learning program migration, optimization, image processing middleware development, and new development of image processing algorithm. We use development environments such as C/C++/Python3/Bash/CUDA C/C++, Linux/Windows, Git/GitHub, and actively engage in research and development in cutting-edge fields.

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Urgent

Edge AI Research and Development Engineer

住友電気工業株式会社

  • CPU
  • AI
  • Python
  • Linux
  • Machine Learning
  • Deep Learning
  • C/C++
  • Django
  • FPGA
  • Image Recognition

We have been involved in the development of image search and security support systems for workplaces using AI technology, as well as research and development of small-scale/high-speed technology and its application. Experience in Python, machine learning, deep learning, and practical experience using Linux is a must.

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Machine Learning Engineer

株式会社フィックスターズ

  • GPU
  • Camera
  • Git
  • Linux
  • Machine Learning
  • C++
  • Data Analysis
  • PyTorch
  • TensorFlow
  • Gitlab

We are looking for new technical proposals such as the use of machine learning technology for data analysis and pattern recognition, prediction and simulation, and the provision of new technologies. Specific tasks include optimizing DNN models for automotive applications, conducting automatic driving recognition system research, using various data for recognition algorithm development, and implementing wide-ranging tasks. The development environment uses C++ and Python3, as well as tools such as pandas, scikit-learn, matplotlib, NumPy, Pytorch, and Tensorflow.

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