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Machine Learning Engineer

株式会社フィックスターズ

  • Machine Learning
  • Linux
  • Data Analysis
  • C++
  • PyTorch
  • Git
  • TensorFlow
  • Scikit-Learn
  • Gitlab
  • Image Recognition
  • pandas
  • NumPy
  • GPU
  • Python3
  • ADAS
  • Autonomous Driving
  • Camera
  • Matplotlib
  • Classification
  • Pattern recognition
  • Machine Learning Technology
  • DNN model
  • march core processor
  • vector instruction
  • Work Location Tokyo
  • Company employee count 101 to 1,000

Company Info

Fujitsu conducts various issues for customers, such as improving the performance of semi-conductor inspection equipment, medical image processing equipment, and external inspection equipment, and practical application of autonomous driving and walking robots. We provide customers with high value that is not available to other companies by actively utilizing low-level software technology, algorithm implementation, and knowledge of various industries and research fields.

Job Summary

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.

Duties

We are actively involved in the provision of new technologies based on data sets received from customers, such as the use of machine learning technology for data analysis and pattern recognition, prediction and simulation, and the provision of new technologies. Specifically, we are conducting research on optimizing DNN models for automotive applications, conducting automatic driving recognition system research, using various data for recognition algorithm development, and implementing wide-ranging tasks. We are also conducting research on the development of DNN for the optimization of specific types of hand-held methods for research, problem solving, and development of evaluation data for the provision of evaluation data for the development of DNN.

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Machine Learning Engineer

株式会社フィックスターズ

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