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 Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day.

Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products.

• Author research papers to share and generate impact of research results across function and in the research community. 
  
• Identify new and upcoming research areas by interacting with potential external and internal collaborators. Help in developing long-term research strategy and plans to expand the impact of Google research. 
  
• Lead research and develop technology for evaluating the consistency, grounding and attribution of generative Large Language Model (LLM) outputs, as well as technology for improving factuality at pretraining, including rerieval augmented generation.
  
• Collaborate with other research teams to expand output verification technology.
  
• Collaborate with Google first-party partner teams to deliver new use cases to production.