【機器學習工程師】Machine Learning Engineer

Positive Grid is devoted to creating cutting-edge technologies to revolutionize the world’s music production. Machine learning team is looking for a proactive, good-communicator and hardworking ML engineer to advance the technologies of guitar/music production. Our projects involve music generation, guitar amp modeling and other machine learning based technologies to extend the Positive Grid’s guitar music creation ecosystem.

【Typical Accountabilities】
- Study Music Generation, Virtual Analog (VA) Modeling (e.g., Amp/Pedal Modeling), Tone -Transfer, and Guitar Tablature Transcription (GTT), guitar/audio relevant machine learning topics
- Cooperate with DSP engineers and product team to develop cutting-edge technology for solving music-related problems
- Develop real-time machine learning inference cross-platform library
- Cooperate with application engineers to integrate machine learning based library

【Essential】
- Master's degree in Computer Science, Electrical Engineering, Mathematics, Physics, or related field
- Experience on RNN, LSTM, CNN, Transformer, AE/VAE, GAN, etc., deep network architectures
- Experience on deep neural network model design and optimization at least two years; have machine learning relevant thesis or had took relevant courses
- Experience on Music Generation, VA Modeling, Tone Transfer or GTT, etc., guitar/music relevant field; experience on NLP or CV is alternative

Development Tool
Strong experience on Python and third-party libraries, e.g., Numpy, SciPy
Hands-on experience on deep learning toolkits such as Tensorflow, Keras, PyTorch, etc.
Experience on Google Colab or Jupyter Notebook
Basic understanding of C++ programming language

【Desirable】
- Familiar with music theory
- Basic understanding of DSP theory
- Working on guitar playing, music production, or software development for the music industry
- Have a strong interest in the guitar or music industry