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Audio Machine Learning Research Engineer Intern

🚀 Off-cycle Internship
💻 Remote

AI generated summary

  • You need a Master's degree or PhD in CS, EE, ML, or Music Tech, strong Python/C++ skills, deep learning experience, collaboration skills, creativity, quick problem-solving abilities, and a background in audio and DSP. Software engineering experience and a publication record are preferred.
  • You will research and implement model compression techniques to optimize deep learning models for audio applications, collaborate with the team to share progress and findings, and work towards maximizing performance on hardware.

Off-cycle Internship

Software Engineering


  • We are seeking a motivated Audio Machine Learning Research Engineer Intern to join our team and contribute to an exciting project focused on improving the performance of lightweight audio machine learning models utilizing model compression techniques such as knowledge distillation, model pruning, and quantization. As a part of our team, you will be immersed in cutting-edge research and development, working at the intersection of audio signal processing, machine learning, and the end-user experience. The duration of this position is 3 months, starting June 2024 (full-time 40 hours/week).


  • Recently graduated from, or is in the process of obtaining a M.S. or PhD in Computer Science, Electrical Engineering, Machine Learning, Music Technology, or a related field.
  • Strong programming background with 2+ years of experience in Python and C/C++.
  • Strong experience in implementing deep neural networks with PyTorch or Tensorflow.
  • Experience with cross-group and cross-culture collaboration.
  • High levels of creativity and quick problem-solving capabilities.
  • Preferred Qualification:
  • Proven software engineer experience via an internship, work experience, and coding competitions.
  • Strong publication record in relevant venues (e.g., ICLR, ISMIR, ICASSP) demonstrating innovative research.
  • Solid understanding and experience working with audio and digital signal processing.

Education requirements

Currently Studying

Area of Responsibilities

Software Engineering


  • Implement and evaluate state-of-the-art model compression techniques to maximize the performance of lighter-weight audio understanding models to enable magical experiences on hardware.
  • Research, implement and evaluate various published approaches and develop new approaches to optimize deep learning models for specific audio problems.­
  • Work closely with the team to share progress, insights, and findings regularly through presentations and discussions.


Work type

Part time

Work mode