Role Overview
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.