Research Scientist, GenAI, Graph Mining
Vienna, Austria
Onsite
mid-level
July 13, 2026
€110,000
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Job Description
Note: Google's hybrid workplace includes remote and in-office roles. By applying to this position you will have an opportunity to share your preferred working location from the following:
In-office locations: Vienna, Austria. Remote location(s): Austria. Minimum qualifications:
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- Experience with the domain area of Generative AI or Large Language Models.
- Experience designing, implementing, and optimizing advanced algorithms.
- One or more scientific publication submission(s) for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
Preferred qualifications:
- 2 years of coding experience.
- 2 years of experience with graph mining.
- 1 year of experience owning and initiating research agendas.
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.
The Graph Mining team's mission is to build the most scalable and accessible graph library to empower teams across Google. We aim for graphs with Xetta-Tera (XT) nodes and Xetta-Xetta-Tera (XXT) edges.
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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Austria: €94000 - €96500 (EUR) + 15% bonus target + equity + benefits
Responsibilities Learn more about benefits at Google .
- Develop end-to-end data evaluation pipelines, curation methods, visualization toolkits, and infrastructure for the Gemini team and Graph Mining library.
- Run experiments with small-scale models and integrate data tools across various applications in a changing environment.
- Requires a mix of C++ and Python development (with large-scale pipeline expertise strongly preferred).
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 .
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