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AI Music Innovation Lead
3 weeks ago
We're seeking an innovative AI Music Expert to spearhead the development of cutting-edge music solutions. Your expertise will drive innovation in music technology.
- Main Responsibilities:
- Design, develop and apply advanced machine learning models for music generation, source separation, audio enhancement and music information retrieval.
- Conduct research on novel machine learning techniques tailored for music and audio applications.
- Deploy machine learning solutions in production environments, powering real-world products and services.
- Collaborate closely with multidisciplinary teams to solve complex problems in music and audio technology.
- A Master's or PhD degree in Computer Science, Machine Learning or a related field (equivalent work experience will also be considered).
- Strong proficiency in Python programming with hands-on experience using ML frameworks such as PyTorch and TensorFlow, and audio processing libraries like Librosa.
- Solid understanding of state-of-the-art ML models and techniques.
- Good understanding of basic music theories such as chords, scales and intervals.
- Familiarity with MIDI and Audio formats including MIDI message structures and audio file formats.
- Strong knowledge in digital signal processing.
- Excellent problem-solving and analytical skills with attention to detail.
- Ability to work both independently and collaboratively in a fast-paced environment.
- Effective communication skills and ability to translate technical concepts to non-technical stakeholders.
- Background or strong interest in music with knowledge of music theory and composition.
- Experience in one or more areas of music AI such as Music Generation, Source Separation, Audio Enhancement, Music Transcription (chords, notes), Singing Voice Synthesis or Music Information Retrieval.
This is a fantastic opportunity for an AI Music Expert to join our team and contribute to the development of innovative music solutions. As a seasoned professional, you'll have a strong record of first-author publications in leading AI conferences or journals and proficiency in C/C++ and shell programming languages with a deep understanding of data structures and algorithm design. Experience with MLOps frameworks such as MLFlow or KubeFlow is highly valued.