Senior Research Scientist

XNote: By applying to this position you will have an opportunity to share your preferred working location from the following: New York, NY, USA; Mountain View, CA, USA.

Minimum qualifications:

• PhD degree in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.
• Experience in research in Deep Learning or Graph Algorithms.
• One or more scientific publication submission(s) for conferences, journals, or public repositories.

Preferred qualifications:

• 1 year of experience leading research efforts and influencing other researchers.
• Experience working on large data and ML, with a strong algorithmic background.
• Experience in large language models or graph mining research.
• Experience coding in Python or C++.
• Ability to be a thought leader in a fast-paced environment with ambiguous requirements, and the ability to quickly learn and adapt to different application domains.

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's mission is to build the most scalable and accessible graph library to empower teams across Google. Recently we have also become actively involved in Gemini Data - making contributions in several areas related to organizing data for Gemini, developing new datasets, and computing value of datasets.

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.
The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

• Develop new methods for efficient dataset evaluation and curation.
• Run experiments with small scale models.
• Develop complete pipelines and a visualization toolkit for data evaluation.
• Integrate and adapt these tools in various applications.
• Contribute to the foundations of the Gemini Data infrastructure and graph mining library.