We are seeking a specialized Machine Learning Engineer with a focus on Audio Signal Processing to join our technical team in Andorra. In this role, you will be responsible for designing and implementing state-of-the-art algorithms for audio analysis, feature extraction, and sound classification. You will bridge the gap between digital signal processing (DSP) and modern deep learning frameworks to solve complex audio-related challenges. Key Responsibilities
Develop and optimize machine learning models for audio processing using PyTorch. Implement robust audio feature extraction pipelines utilizing Librosa and other DSP libraries. Research and apply the latest techniques in sound classification, source separation, or speech enhancement. Collaborate with data engineers to build scalable data processing pipelines for large audio datasets. Deploy and maintain ML models in production environments, ensuring high performance and low latency. Required Qualifications
3+ years of professional experience in Machine Learning or Data Science. Deep expertise in Python programming and the PyTorch ecosystem. Proven experience with audio-specific libraries such as Librosa, Torchaudio, or Essentia. Strong understanding of Digital Signal Processing (STFT, Mel-spectrograms, MFCCs). Background in training and fine-tuning neural network architectures (CNNs, RNNs, Transformers). Nice-to-Have
Experience with C++ for real-time audio processing. Familiarity with cloud platforms (AWS/GCP/Azure). Contributions to open-source audio or ML projects.
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