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August 7, 2025

Research Scientist, Translate Research

Mid • On-site

$141,000 - $202,000/yr

Mountain View, CA

Minimum qualifications:

  • PhD degree in Computer Science, a related field, or equivalent practical experience.
  • Experience in machine translations or related Natural Language Processing tasks.
  • Experience with Machine Learning or Evaluations.
  • One of more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

  • 2 years of experience in coding.
  • 1 year of experience owning and initiating research agendas.
  • Experience with Machine Translation or Multilingual Natural Language Processing.

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.

Google Translate's mission is to reduce the language barrier by translating text, speech when needed, making content more accessible to people. Our team’s main goal is to produce high quality translation models for Google Translate. These models are used by billions of users and integrated into products across Search, Cloud, Chrome, Android, Ads, and YouTube.

This posting is specific for the Translate Research sub-team which focuses on improving translation and non-English capabilities within LLMs including training multilingual LLMs from scratch.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

The US base salary range for this full-time position is $141,000-$202,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. 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

  • Work within a team on research problems that are important for Google Translate.
  • Research novel techniques for improving translation quality via modeling, data selection, and model tuning.
  • Design and conduct experiments for model quality improvements, analyze results, and determine steps for moving forward.
  • Develop and invent new machine translation techniques that improve the translation quality of Google Translate.
  • Invent reliable automatic and human evaluation methods for machine translation outputs, and integrate findings into the machine translation model.