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Google Audio Jobs (NOW HIRING)

Powered by realistic state-of-the-art 3D imaging and spatial audio and integrated with today's leading remote video platforms, Google Beam enables you to be immersed in the moment, together. As a ...

Position Overview The PCC Audio Visual Technician's role is to support properties that AV Concepts ... Proficient with Google Drive (Doc and Sheets), PowerPoint and Outlook. * Must be willing to work ...

Position Overview The PCC Audio Visual Technician's role is to support properties that AV Concepts ... Proficient with Google Drive (Doc and Sheets), PowerPoint and Outlook. * Must be willing to work ...

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Google Audio information

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$29.5K

$84.5K

$171.5K

How much do google audio jobs pay per year?

As of Sep 6, 2026, the average yearly pay for google audio in the United States is $84,456.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,000.00 and $113,000.00 per year, depending on experience, location, and employer.

What is a Google Audio?

A Google Audio job typically involves working on audio-related technologies, such as speech recognition, sound processing, and audio AI. This can include roles in research, engineering, product design, or content creation for platforms like Google Assistant, YouTube, or Google Podcasts. Employees in these roles develop algorithms, improve voice recognition accuracy, or enhance sound quality across Google’s products. Depending on the position, responsibilities may also include machine learning, UX development, or working with music and audio content partnerships.

What does a Google Audio do?

In a Google Audio position, you can expect to work on researching, designing, and optimizing audio algorithms and technologies for use in products such as Google Assistant, Pixel devices, or YouTube. Day-to-day tasks may include coding, analyzing audio data, running experiments, and collaborating with UX designers, product managers, and other engineers. You'll often participate in meetings to discuss project requirements and share progress, and may also contribute to technical documentation or present findings. The work environment is highly collaborative, with opportunities to innovate and regularly interact with colleagues across various specialties.

What are the key skills and qualifications needed to thrive in the Google Audio position, and why are they important?

To thrive in a Google Audio role, you need a background in audio engineering, digital signal processing, and computer science, often supported by a relevant degree or experience with audio technology. Familiarity with tools such as Python, C++, TensorFlow, and audio editing software, as well as experience with machine learning frameworks, is highly valued. Creative problem-solving, strong communication, and the ability to collaborate within cross-functional teams help individuals excel in this environment. These skills are crucial for developing innovative audio products and solutions that meet Google's high standards for user experience and technological advancement.

More about Google Audio jobs

What cities are hiring for Google Audio jobs?

Cities with the most Google Audio job openings:

What are the most commonly searched types of Google Audio jobs?

The most popular types of Google Audio jobs are:

What states have the most Google Audio jobs?

States with the most job openings for Google Audio jobs include:

Infographic showing various Google Audio job openings in the United States as of August 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 70% Physical, 3% Hybrid, and 27% Remote job distribution, with an average salary of $84,456 per year, or $40.6 per hour.

Research Scientist, Gemini Audio i18n, DeepMind

DeepMind

Mountain View, CA • On-site

Full-time

Posted 25 days ago


Key responsibilities

  • Create comprehensive evaluation sets and benchmarks to measure audio-to-audio (A2A) model performance across international languages, accents, and regional dialects.

  • Propose, prototype, and evaluate novel modeling techniques to improve A2A audio understanding, dialog, and audio generation capabilities with a focus on scalability.

  • Identify performance gaps in current multilingual audio models and collaborate with cross-functional research and engineering teams to deploy solutions.


Job description

info_outline
X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA.
Minimum qualifications:
  • Bachelor's degree in Computer Science, Speech Recognition, Computational Linguistics, a related technical field, or equivalent practical experience.
  • Experience conducting research or development in Speech Recognition, Text-to-Speech (TTS), or Large Language Models (LLMs).
  • Experience coding in Python or C and using deep learning frameworks such as PyTorch, JAX, or TensorFlow.
  • Experience working with audio data, speech processing, or multilingual datasets.

Preferred qualifications:
  • Master's degree or Ph.D. in Automatic Speech Recognition (ASR), Text-to-Speech (TTS), Computational Linguistics, or a related field.
  • 3 years of experience in Large Language Models (LLMs) or multimodal foundation models.
  • Experience developing audio-to-audio (A2A) architectures, end-to-end speech models, or spoken dialog systems.
  • Experience scaling speech models across international languages, accents, or low-resource locales.
  • Publication record in speech or machine learning conferences (e.g., ICASSP, INTERSPEECH, NeurIPS, or ACL).

About the job
As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
Artificial intelligence will be one of humanity's most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.
We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $174000 - $252000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities
  • Create comprehensive evaluation sets and benchmarks to measure audio-to-audio (A2A) model performance across international languages, accents, and regional dialects.
  • Propose, prototype, and evaluate novel modeling techniques to improve A2A audio understanding, dialog, and audio generation capabilities with a focus on scalability.
  • Identify performance gaps in current multilingual audio models and collaborate with cross-functional research and engineering teams to deploy solutions.

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