In a world where technology advances in an exponential rate, the human-machine interface is still mostly confined to the visual and tactile senses. In contrast, for human-to-human interaction we heavily rely on speech. In addition, the auditory information is very useful for humans in detecting a variety of situations, including hazardous ones. Recently, the interest in voice human-machine interface, and in audio inference has grown dramatically.
At the same time, Deep Neural Network (DNN), or Deep Learning (DL), based algorithms are proving useful and superior to ""classical"" approaches in many fields, including vision, speech, natural language, cyber security, business, bio-medical, and so on.
In this role you will work in a team that seeks, studies and develops state of the art DL algorithms oriented mainly on voice and sound, but not limited to that.
Requirements:
-Masters degree or equivalent practical experience.
-Knowledge in Deep Neural Networks.
-Knowledge in signal processing (e.g. audio/speech, vision, sensor arrays, etc.).
-Familiar with Python.
-Strong self-learning ability.
Advantageous Qualifications
-PhD degree.
-General knowledge in Machine Learning.
-Experience with a NN framework such as TensorFlow / Caffe2 / PyTorch / Keras.
-Experience (including academic) in audio/speech signal processing.
-Experience in development for Android.
-Familiar with Unix / Linux systems.
-Strong object-oriented design and coding skills.