ML Audio Researcher — Open Ear & Superhuman Hearing

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

Job summary

Google LLC in the United States seeks a Share ML Research Scientist, Audio Algorithms to advance ML research for audio applications across Irvine and Mountain View. You will lead exploratory work on Open Ear Inteligibility and Superhuman Hearing, balancing feasibility with high-impact innovations.

Applicants should have a PhD or equivalent, 2+ years leading research, and experience with ML for audio using JAX or TensorFlow. Collaborative, impact-driven environment with competitive compensation.

Qualifications

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

Responsibilities

• Lead exploratory research into Open Ear Inteligibility and Superhuman Hearing for humans and machines.
• Work on transformational audio bets for Pixel and Buds.
• Prioritize feasibility and foundation elements of agentic audio experiences.
• Collaborate with the Applied Research team to deliver impact-first innovation.

Skills

Machine learning for audio

Deep learning

C++ / Python

Research leadership

Education

PhD in CS or related field

Tools

JAX

TensorFlow

Job description

Google LLC in the United States seeks a Share ML Research Scientist, Audio Algorithms to advance ML research for audio applications across Irvine and Mountain View. You will lead exploratory work on Open Ear Inteligibility and Superhuman Hearing, balancing feasibility with high-impact innovations.

Applicants should have a PhD or equivalent, 2+ years leading research, and experience with ML for audio using JAX or TensorFlow. Collaborative, impact-driven environment with competitive compensation.