Speech/Audio Machine Learning Engineer

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.

Responsibilities:

• 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.

Qualifications

• 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.