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.

Our team is committed to developing advanced methodologies tailored specifically for multilingual environments. We focus on pre-training multilingual models, enhancing the quality of multilingual instruction-tuning datasets, refining multilingual evaluation processes, boosting knowledge transfer across languages, and optimizing multilingual tokenization among other initiatives.

The Technology & Society organization connects research, people, and ideas across Google and Alphabet to help shape and advance our most ambitious technology innovations and initiatives and their impact on users and society for the better, and responsibly. In addition, we also aim to share perspectives, engage, and collaborate with others externally on technology related issues and opportunities for society.

• Author research papers to share and generate impact of research results across the team and in the research community. 
  
• Research and develop technology for improving multilingual Large Language Models (LLM) such as instruction-tuning, pre-training, multilingual reasoning.
• Research and develop technology for pre-training LLMs for target languages other than English.
  
• Collaborate with other research teams to expand multilingual LLM technology.
  
• Collaborate with Google first-party partner teams to deliver new multilingual technologies to production.