Machine Learning Engineer, Audio, GenAI, Pixel

Mountain View, California


Employer: Google
Industry: Hardware Engineering
Salary: Competitive
Job type: Full-Time

Minimum qualifications:

  • Bachelor's degree in Computer Science, Electrical Engineering, Computer Engineering, Physics, a related field (e.g., Optics, Sensors, Audio/DSP, etc.), or equivalent practical experience.
  • 4 years of experience working in a consumer hardware technical environment, or 3 years of experience with an advanced degree.
  • Experience with ML/AI algorithms and tools, deep learning or natural language processing.
  • Experience with audio applications using LLMs, audio tokenization, and similar technologies.


Preferred qualifications:

  • Master's degree or PhD in Electrical Engineering, Computer Engineering, Physics, or a related field (e.g., Optics, Sensors, Audio/DSP).
  • 7 years of experience with consumer hardware, producing new technology.
  • Experience with Generative Audio Modeling, Multimodal modeling, On-device AI Implementation or Fine tuning for LLMs


About the job

The TechEng team is a central technology innovation group in Devices & Services dedicated to developing innovative and strategic solutions across the Devices Portfolio for Google. This includes Pixel Phones, Pixel Buds, Watches, and Home (e.g., tablets, trackers, etc.). We leverage our deep understanding of the portfolio to design and implement innovative solutions that align hardware, software, and AI/ML capabilities.

In the Audio Applied Research Group, we focus on audio, speech, media fundamentals, quality, and bringing differentiation to the Pixel portfolio. We work on taking novel ideas and delivering them via cutting edge research and development as well as seeing those through launch.

In this role, you'll be responsible for developing the machine learning system and models that power the Pixel audio advancements, particularly LLM fine tuning and leveraging Gemini for audio use cases. This includes tasks such as data collection design, data engineering, feature engineering, model training, and model evaluation. You will work with engineers, researchers, and product managers across Google to design and implement new features for the personal audio experience.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

The US base salary range for this full-time position is $142,000-$211,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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

  • Address challenging audio research and engineering problems at the very cutting edge of GenAI that can be deployed on Google's hardware portfolio (e.g., phones, watches, earbuds, tablets, etc.).
  • Conduct applied research figuring out research developments best suited to solve open-ended problems on hardware devices.
  • Break down challenging problems to make iterative progress.
  • Build end to end ML systems spanning data, modeling, evaluation, before handing off to deployment on-device.

Created: 2024-09-11
Reference: 88091359189050054
Country: United States
State: California
City: Mountain View


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