Google is looking to solve the problem of developing and optimizing machine learning models for audio use cases across Pixel product lines, and innovating audio pipelines through both offline simulation and real-time on-device hardware.
Requirements
- Experience in Python programming and ML framework (e.g., TensorFlow, JAX, and PyTorch).
- Experience with International Conferences such as ICASSP, Interspeech, etc.
- Experience in generative Audio Models and Audio Source Separation.
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 2 years of experience leading a research agenda.
- One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
- 2 years of coding experience.
Responsibilities
- Own Machine Learning model development including model training and optimization.
- Contribute to model inference optimization into Android Kernel/HAL and audio and speech algorithms development process.
- Design and fine tune ML models for Pixel devices.
- Contribute to prototyping to delivery for audio features.
- Collaborate with Android Pixel Audio and Google Silicon teams for feature development.
- Setup large-scale tests and deploy promising ideas quickly and broadly.
- Develop new and improved products, processes, or technologies.
Other
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 2 years of experience leading a research agenda.
- One of more scientific publication submission(s) for conferences, journals, or public repositories.
- Collaborate with partner teams such as Google DeepMind and Google Silicon teams.
- Interact with research programs at partner universities and technical institutes all over the world.
