Research Scientist, GenAI, Graph Mining
Indexed description
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.).
- 2 years of coding experience.
- 2 years of experience with graph mining.
- 1 year of experience owning and initiating research agendas.
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).
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