Info_outlineXNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Zürich, Switzerland; London, UK.
Minimum qualifications:
* PhD degree in Computer Science, a related field, or equivalent practical experience.
* Research experience on marketplace design and online selection algorithms.
* Research experience on data mixture optimization for LLMs.
* Experience with Python and C++ programming.
* Experience with Graph Mining models and Machine Learning applications.
* One or more accepted scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
Preferred qualifications:
* Experience with Large Language Models.
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.
Our team conducts research at the intersection of auction theory, mechanism design, advanced algorithms, and machine learning to build economically and computationally efficient marketplaces. We collaborate with teams across Google globally to deliver high-impact solutions in advertising (search and display), data markets, and market-based resource allocation.
Currently, our primary focus is the Economics of GenAI. We are central to the Gemini Data initiative, where we contribute to organizing Gemini's data mixture, developing novel datasets, and pioneering methodologies to compute the value of specific data assets.
Responsibilities
* Apply AI and ML techniques to innovate auction formats and dynamic pricing strategies.
* Apply AI and ML techniques to innovate auction formats and dynamic pricing strategies.
* Design and implement novel methodologies for the pricing and valuation of large-scale datasets.
* Partner with Ads, Cloud, Search, and Gemini teams to move projects from theoretical proofs-of-concept to global production.