Minimum qualifications:- Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, or a specialized field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
- 4 years of experience working in a Machine Learning technical environment.
Preferred qualifications:- Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
- Experience designing and implementing real-time ML based voice processing algorithms for embedded systems or mobile platforms.
- Technical leadership experience: setting direction, driving business impact.
- Expertise in generative AI and speech research, including first-author publications at top AI conferences (e.g., NeurIPS, ICML, InterSpeech, etc.).
- Proven track record of optimizing algorithms for performance and low latency.
About the jobAs an Applied AI Engineer in the Audio Applied AI Research and Innovation team, you will be at the forefront of defining the future of audio for the Pixel ecosystem. Our mission is to push the boundaries of audio AI, advancing the state-of-the-art in playback, capture, generation, enhancement, and ambient understanding. This role is defined by research-driven innovation and strong engineering principles, where you will bridge the gap between fundamental AI research and deployment in hardware-constrained environments. You will conduct applied research to solve complex audio challenges, working in a highly collaborative environment with cross-functional hardware and software teams to translate research breakthroughs into impactful features for phones, wearables, and future devices.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $159000 - $231000 (USD) 15% bonus target bonus equity benefits
Learn more about benefits at Google .
Responsibilities- Innovate in audio machine learning through fundamental and applied research, advancing the state-of-the-art in audio playback, capture, generation, and editing.
- Research and develop novel ML models for speech recognition, text-to-speech generation, and real-time speech enhancement.
- Design and implement generative models specifically for signal restoration, enhancement, and ambient audio understanding.
- Architect, prototype, and scale robust ML architectures for deployment across on-device (mobile/wearable) and cloud platforms.
- Collaborate with cross-functional hardware and software teams to translate research breakthroughs into integrated product features.
