Lead ML Audio Research Scientist - Real-Time Perception

Google; Mountain View (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google is hiring for a high-velocity Applied Research role focused on transformational audio bets for Pixel and Buds. You will lead exploratory, non-timeline-driven research into Open Ear Inteligibility and Superhuman Hearing, prioritizing massive user differentiation over specific methods.

Individual pay is determined by skills, experience, and education. The position offers equity, benefits, and a 15% bonus target for US candidates.

Qualifications

• PhD in Computer Science or related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.
• Experience developing and training machine learning algorithms for audio applications.
• Experience with deep learning frameworks such as JAX or TensorFlow applied to signal processing tests.
• Publications in conferences, journals, or public repositories (e.g., CVPR, NeurIPS, ICML, ICLR).

Responsibilities

• Develop real-time algorithms for moonshot audio initiatives beyond immediate product timelines.
• Architect first-principles algorithms bridging theory and validated prototypes, proving feasibility before scaling.
• Prioritize impact and massive user differentiation, with agile pivots when necessary.
• Foster a Shielded but Connected research environment, guiding core execution teams on long-term issues.
• Collaborate with a small group of researchers to define the foundations of next‑generation agentic audio.

Skills

Audio ML research leadership

Publications in top venues

Research leadership experience

Education

PhD in Computer Science or related field

Tools

JAX

TensorFlow

C++

Python

Job description

Google is hiring for a high-velocity Applied Research role focused on transformational audio bets for Pixel and Buds. You will lead exploratory, non-timeline-driven research into Open Ear Inteligibility and Superhuman Hearing, prioritizing massive user differentiation over specific methods.

Individual pay is determined by skills, experience, and education. The position offers equity, benefits, and a 15% bonus target for US candidates.