Job Type
Job Details
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 4 years of experience with research agendas across multiple teams or projects.
- Experience in Natural Language Processing (NLP) research.
- One or more scientific publication submissions for conferences, journals, or public repositories.
Preferred qualifications:
- PhD in NLP with a track record of 50 h-index or more.
- 2 years of experience in coding and leading multiple research efforts and influencing research direction.
- Experience with modern LLMs and generative text models.
- Experience in driving research in the industry.
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.
- 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 augmented generation.
- Collaborate with other research teams to expand output verification technology.
- Collaborate with Google first-party partner teams to deliver new technology to production.
- Drive academic-quality research that would result in conference publications
