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About the role
Join a new, high-velocity "startup-style" Applied Research team within TechEng dedicated to transformational audio bets for the next decade of Pixel and Buds. You will lead exploratory, non-timeline-based research into Open Ear Inteligibility and Superhuman Hearing for humans and machines.
What they're looking for
- PhD in Computer Science, a related field, or equivalent practical experience
- 2 years of experience leading a research agenda
- Experience developing and training machine learning algorithms specifically for audio applications (e.g., neural noise suppression, acoustic modeling, or speech enhancement)
- Experience with deep learning frameworks such as JAX or TensorFlow applied to signal processing tests
- One or more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.)
More about this role
- Develop new and advanced algorithms for "moonshot" audio initiatives specifically real time perception for humans and AI operating outside the gravitational pull of immediate product timelines.
- Architect first-principles algorithms that bridge the gap between theoretical research and validated prototypes, proving feasibility before scaling.
- Adopt an impact-first philosophy, prioritizing massive user differentiation and maintaining the agility to pivot when technical paths do not yield high-order breakthroughs.
- Foster a "Shielded but Connected" environment, protecting the team's research velocity while providing technical guidance to core execution teams on future-decade issues.
- Collaborate alongside a small group of researchers (including Principal-level leadership) to define the foundational elements of next-generation agentic audio.
- PhD in Computer Science, a related field, or equivalent practical experience.
- 2 years of experience leading a research agenda.
- Experience developing and training machine learning algorithms specifically for audio applications (e.g., neural noise suppression, acoustic modeling, or speech enhancement).
- Experience with deep learning...
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