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.

In this role, you will work on multilingual Natural Language Processing (NLP) for low resource languages. This project aims to develop multilingual Large Language Models (LLMs), and their application to translation and semantic understanding tasks. You will build several existing/in-development datasets, and also construct several additional resources, including multimodal text and audio. You will create novel evaluation datasets, compile and create new datasets, and develop algorithms for LLM training and evaluation.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

• Design algorithms for model training and prediction.
  
• Manage experiments on Tensor Processing Unit (TPU) cloud.
  
• Write up results in design documents, technical reports, and papers for publication.
  
• Propose new research ideas and provide research leadership in the team.
  
• Write programs in Python with JAX and PAX.