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Salary
≈ $30k – $69k per year (Estimated)
Location
In office (New Taipei)
Seniority
Staff · 5+ years exp

Confirmed on the employer's own hiring board on Oct 18, 2026. First seen by Alion on Oct 1, 2026. Google scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Google is an American technology company founded in 1998 by Larry Page and Sergey Brin and now the principal subsidiary of Alphabet, headquartered in Mountain View, California. It operates the world's dominant search engine and the advertising system built around it, along with YouTube, Android, Chrome, Gmail, Maps, Workspace and Google Cloud, reaching billions of users across nearly every internet-connected market. The company designs its own silicon in the Tensor Processing Unit line, develops the Gemini foundation models through Google DeepMind, and derives most of its revenue from advertising while cloud has become its fastest growing segment.

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.

As a Staff Research Scientist in Android Pixel Audio, you will be responsible for algorithm development for audio use cases across Pixel product lines. You will innovate, execute and validate audio pipelines through both offline simulation and real-time on-device hardware. You will be interacting with partner teams such as DeepMind and Google Silicon teams to design and modify the algorithms and software layers to impact the upcoming Google audio technology roadmap across the Pixel ecosystem.The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

Responsibilities

  • Own machine learning model development including model training and optimization.
  • Contribute to model inference optimization into Android Kernel/HAL and audio and speech algorithms development process.
  • Design and fine tune Machine Learning (ML) models for Pixel devices.
  • Contribute to prototyping to delivery for audio features.
  • Collaborate with Android Pixel Audio and Google Silicon teams for feature development.

Qualifications

Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • 4 years of experience with research agendas across multiple teams or projects.
  • One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

  • 5 years of experience with software development in one or more programming languages, or 3 year of experience with an advanced degree.
  • Experience with machine learning principles and model architectures.
  • Experience in audio and speech related model development and inference.
  • Multiple scientific publications at audio/signal processing/speech/ML research conferences, journals, or public repositories.
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