Speech/Audio Machine Learning Engineer

Job description

Position Overview:

We are seeking a talented and innovative Machine Learning expert to join our Audio AI team. As a Speech/Audio Machine Learning Engineer, you will play a crucial role in developing cutting-edge audio software solutions, leveraging machine learning techniques to enhance audio processing and analysis. You will work closely with a multidisciplinary team of engineers, data scientists, and audio experts to create groundbreaking products that push the boundaries of audio technology. This is a unique opportunity to contribute to the development of next-generation audio software and make a significant impact in the industry.


  • Collaborate with cross-functional teams to design and implement machine learning models and algorithms for audio processing, analysis, and enhancement.
  • Train, validate, and fine-tune machine learning models for various applications.
  • Evaluate and benchmark the performance of machine learning models using appropriate metrics and statistical techniques.
  • Collaborate with software engineers to integrate machine learning algorithms into audio software products and ensure seamless functionality and performance.
  • Debug and troubleshoot issues related to machine learning algorithms and audio software applications.
  • Document software development processes, algorithms, and experiments, and communicate findings and recommendations to the team effectively.


  • Required to have a Ph.D. degree.
  • Must have Strong programming skills in Python and Matlab, with experience in audio processing libraries (e.g., librosa, torch audio, or similar).
  • Must understand machine learning techniques, including deep learning architectures (e.g., CNNs, RNNs, GANs) and relevant frameworks (e.g., PyTorch).
  • Expected to have >=5 years of experience in developing and deploying machine learning models for audio-related applications.
  • Must be proficiency in data preprocessing, feature extraction, and data augmentation techniques for audio.
  • Familiarity with audio signal processing concepts, such as Fourier analysis, spectral modeling, and time-frequency representations is essential.
  • Expected to have trong problem-solving skills and ability to think creatively to devise innovative solutions to audio-related challenges is required.
  • Excellent communication in English is mandatory.

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