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. As the fourth founding member of this group, you will lead exploratory, non-timeline-based research into Open Ear ANC and Superhuman Hearing.
We operate under a "shielded but connected" model—protected from the gravitational pull of daily product cycles to focus on pure feasibility and first-principles innovation. You will adopt an impact-first philosophy, ruthlessly prioritizing massive user differentiation to prove the "impossible" and define the foundational elements of agentic audio experiences.
The US base salary range for this full-time position is $237,000-$329,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Lead algorithm feasibility research for "moonshot" audio initiatives—specifically Superhuman Hearing—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 strategic technical guidance to core execution teams on future-decade challenges.
- Collaborate as a founding technical pillar alongside a small group of researchers (including principal-level leadership) to define the foundational elements of next-generation agentic audio.
Qualifications
Minimum qualifications:
- Bachelor’s degree in Machine Learning, Electrical Engineering, Computer Science, or a related technical field, or equivalent practical experience.
- 8 years of experience developing machine learning algorithms specifically for audio applications (e.g., neural noise suppression, acoustic modeling, or speech enhancement).
- Experience in algorithm implementation and prototyping using C++ and Python.
- Experience with deep learning frameworks such as JAX, TensorFlow, or PyTorch applied to signal processing challenges.
Preferred qualifications:
- PhD in Machine Learning, Electrical Engineering, Signal Processing, Acoustics, or a related field.
- Experience navigating high-ambiguity research environments where the priority is delivering massive user differentiation over a specific method.
- Experience in developing foundational elements for agentic audio, such as Open Ear ANC or Superhuman Hearing/Perception.
- Ability to operate as the fourth founding member in a lean, high-velocity team, maintaining a "shielded but connected" partnership with core engineering to guide future product execution.
- A proven track record of moving theoretical ML-audio research into hardware-validated prototypes or real-world product proofs-of-concept.