- PhD in Computer Science with an emphasis on Machine Learning, Data Science, or equivalent practical experience
- Experience with Python
- Experience in Machine Learning research
- Experience creating and leading a research agenda
- Experience in application of machine learning in safety
- Experience in developing novel research for foundational models
- Engineering skills in Python
About the job
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.
- Create a research agenda in the context of safety for large models.
- Work with Research Engineers to design and develop Machine Learning models and pipelines, in either the text or multi-modal context.
- Create new methods for either language or multi-modal data, especially within the context of safety for large models. Design large-scale experiments and evaluate them on safety datasets.
- Prepare high-quality research publications for peer-reviewed conferences and journals.
- Contribute to the design, implementation and debugging of high quality, scalable, reliable, and easy-to-use frameworks for end-to-end ML.
Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy
and EEO is the Law.
If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form