Google is looking to solve business and technical problems related to algorithm development for audio use cases across Pixel product lines, aiming to innovate, execute, and validate audio pipelines through both offline simulation and real-time on-device hardware. This involves interacting with partner teams to design and modify algorithms and software layers impacting the future of Google's audio technology roadmap within the Pixel ecosystem.
Requirements
- Experience in Python programming and ML framework (e.g., TensorFlow, JAX and PyTorch).
- Experience in generative audio models and audio source separation.
- 2 years of coding experience.
- One or more scientific publication submission(s) for conferences, journals or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
- Experience with International Conferences such as ICASSP, Interspeech, etc.
Responsibilities
- Own machine learning model development including model training and optimization.
- Contribute to model inference optimization in Android Kernel/HAL and in audio and speech algorithm development.
- Design and fine tune ML models for Pixel devices.
- Contribute to the entire lifecycle of audio features, from prototyping to delivery.
- Collaborate with Android Pixel Audio and Google Silicon teams for feature development.
- setup large-scale tests and deploy promising ideas quickly and broadly
- applying the latest theories to develop new and improved products, processes, or technologies
Other
- 2 years of experience leading a research agenda.
- 1 year of experience leading research efforts and influencing other researchers.
- PhD degree in Computer Science, a related field or equivalent practical experience.
- PhD in Electrical and Computer Engineering, Acoustics or similar field.
