Research Scientist, Graph Mining, GenAI, Google Research - Google

New York, NY

About the Job

Note: 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 or Computer Engineering, a similar technical field of study (e.g., Electrical Engineering, Mathematics, Information Technology), or equivalent practical experience.
2 years of experience leading a research agenda.
1 year of experience with software development in one or more programming languages (e.g., Python, C, C++, Java).
Research experience in Deep Learning or Graph Algorithms.

Preferred qualifications:

Experience in large language models or graph mining research.
Understanding of Algorithms.

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 XT nodes and XXT edges. In the past 13 years, we empowered 70+ teams, 250+ launches across the company, with 200+ publications, specialized in Anti-Abuse, Duplicate Detection, Keyword Targeting, Image Understanding, and more, built scalable tools for graph-based Building, Learning, Clustering, Sampling, Convolutional Networks, Label Propagation, Partitioning, Similarity Ranking, and Visualization. We became 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, developing new methods for integration of structured data and GenAI and running experiments with small scale models.
Develop pipelines and visualization toolkits for data evaluation, contributing to the foundations of Gemini Data infrastructure, and integrating and adapting these tools in various applications.
Contribute to the Graph Mining library.
Develop large-scale pipelines.
Work involves a combination of C++ and Python development.

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.

Source : Google