• Implementing novel deep neural network architectures and learning techniques to solve a variety of audio related tasks and push the state of the art in performance.
  • Research and develop advanced audio applications including speech recognition, voice recognition, voice wakeup using state of art deep learning algorithms.
  • Research and develop advanced audio signal processing algorithms including noise cancellation, localization, acoustic detection, acoustic fingerprinting.
  • Analyze and optimize audio signal processing and deep learning algorithms on mobile/embedded devices, e.g., using hardware acceleration such as GPU/DSP.

Essential Requirements

  • M.S. in Computer Science, Machine Learning, Electrical Engineering, Robotics or similar field (Ph.D. is preferred).
  • Solid understanding on audio signal processing.
  • Solid understanding and experience of applying deep learning to real problems in the fields of voice recognition, speech recognition, and other audio related applications.
  • Holistic understanding of deep learning concepts, state of the art in audio processing research and the mathematics of machine learning. Familiar with CNN, RNN, LSTM.
  • Strong experience in C/C++ programing.
  • Hands-on experience in deep learning frameworks, e.g., OpenCV, Tensorflow, Keras, Pytorch, and Caffe.
  • Ability to quickly adapt to new situations, learn new technologies, and collaborate and communicate effectively.
  • 3+ years of industry experience with deep learning algorithm development and optimization.
  • Experience with parallel computing, GPU/CUDA, DSP, and OpenCL programming is a plus.
  • Top-tier conference publication records, including but not limited to CVPR, ICCV, ECCV, NIPS, ICML, is a strong plus.

技能標籤: deep learning, machine learning