Job Type
Job Details
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- Experience with Machine Learning algorithms and tools (e.g., TensorFlow), artificial intelligence and natural language processing.
- One or more scientific publications for conferences, journals, or public repositories.
Preferred qualifications:
- PhD degree in Natural Language Processing, Generative AI, or related fields.
- Experience with modern large language models and generative models.
- Experience in research factuality, grounding and evaluation of large language models.
- Publication track in related Generative AI fields in conferences.
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 be working on improving the factuality of Google's large language models that power prominent google products such as search AI overviews, gemini chat, cloud and YouTube.
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.
- Perform research for improving large language model (LLM) factuality and it's grounding capabilities.
- Collaborate with other research teams to improve large language model (LLM) factuality.
- Integrate innovative research into google products by collaborating with product teams.
