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Machine Learning Engineer, Audio, Project Starline

AT Google
Google

Machine Learning Engineer, Audio, Project Starline

San Francisco, CA

Minimum qualifications:

  • Bachelor's degree or equivalent practical experience.
  • 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
  • 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  • Experience with machine learning principles and deep learning architectures.
  • Experience with audio signal processing, speech enhancement, or sound separation concepts.
  • Experience analyzing problems, designing solutions, and implement them with quality code.
Preferred qualifications:
  • Master's degree or PhD in Computer Science or related technical field.

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  • 1 year of experience in a technical leadership role.
  • Experience with real-time audio processing and optimization techniques.
  • Experience working with and evaluating audio or speech processing ML models.
  • Experience in Python programming and deep learning frameworks (e.g., JAX, Keras, etc.).

  • About the job

    Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

    As a Machine Learning Engineer on the Starline audio team, you will play a role in shaping the future of immersive audio experiences. You will be responsible for training, evaluating, and optimizing AudioLM-based models that push the boundaries of speech enhancement and sound separation. You will directly contribute to creating an immersive and realistic audio environment for Starline users, blurring the lines between physical and virtual presence. You will contribute to the ongoing development and maintenance of the audio infrastructure, ensuring seamless integration and real-time performance of the audio processing pipeline.

    Project Starline from Google combines advances in hardware and software to enable friends, families and co-workers to feel together, even when they're cities (or countries) apart. Imagine looking through a magic window, and through that window, you see another person, life-size and in three-dimensions. As part of the Project Starline team, you'll work with researchers and engineers in a fast-paced product-oriented environment. Our teams collaborate closely with Google Workspace and Research teams. Your contributions will have an impact on the future of communications with Google products. You will apply technology to solve that really important problem that we often want to be together and we can't.

    The US base salary range for this full-time position is $161,000-$239,000 + 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

    • Train, evaluate, and fine-tune AudioLM-based models for speech enhancement, sound separation, classification, and remixing.
    • Optimize model inference for real-time, low-latency performance on both CPU and GPU platforms.
    • Design and implement data processing pipelines to prepare and augment training data.
    • Work with research scientists, audio engineers, and software developers to integrate models into the Starline system and launch audio features.
    • Contribute to the development and maintenance of the audio infrastructure in C++, ensuring scalability, reliability, and efficiency.

    Client-provided location(s): San Francisco, CA, USA; Mountain View, CA, USA
    Job ID: Google-109467585367417542
    Employment Type: Full Time

    Perks and Benefits

    • Health and Wellness

      • Health Insurance
      • Dental Insurance
      • Vision Insurance
      • Life Insurance
      • Short-Term Disability
      • Long-Term Disability
      • FSA
      • HSA
      • Fitness Subsidies
      • On-Site Gym
      • Mental Health Benefits
      • Health Reimbursement Account
      • HSA With Employer Contribution
    • Parental Benefits

      • Birth Parent or Maternity Leave
      • Non-Birth Parent or Paternity Leave
      • Fertility Benefits
      • Adoption Assistance Program
      • Family Support Resources
      • Adoption Leave
    • Work Flexibility

      • Hybrid Work Opportunities
    • Office Life and Perks

      • Commuter Benefits Program
      • Casual Dress
      • Pet-friendly Office
      • Snacks
      • Some Meals Provided
      • On-Site Cafeteria
    • Vacation and Time Off

      • Paid Vacation
      • Paid Holidays
      • Personal/Sick Days
      • Leave of Absence
      • Volunteer Time Off
    • Financial and Retirement

      • 401(K) With Company Matching
      • Company Equity
      • Performance Bonus
      • Financial Counseling
    • Professional Development

      • Tuition Reimbursement
      • Internship Program
      • Learning and Development Stipend
    • Diversity and Inclusion

      • Employee Resource Groups (ERG)

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