Senior Research Scientist, Interactive Recommender Systems, Google Research
- linkCopy link
- emailEmail a friend
Minimum qualifications:
- PhD degree in Computer Science, a related field, or equivalent practical experience.
- 2 years of experience leading a research agenda.
- Research experience with one or more of the following: multi-agent systems, algorithmic mechanism or market design, recommender systems, reinforcement learning or active learning, generative AI.
- One or more scientific publication submission(s) for conferences, journals, or public repositories.
Preferred qualifications:
- 2 years of coding experience.
- 1 year of experience leading research efforts and influencing other researchers.
- Experience with programming in C, C++, or Python.
- Experience with Machine Learning methods.
- Excellent publication record.
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 is focused on research to develop the next generation of technologies to power systems and other user-facing products at Google, with an emphasis on improving long-term user satisfaction in complex ecosystems. We pay special attention to interactive systems, such as conversation recommender systems, and the use of generative models; long-term, sequential optimization, using techniques such as reinforcement learning; personalization via user preference modeling and elicitation; and modeling multi-agent interactions, incentives and content creation using game theory and mechanism design. We collaborate directly with product teams to both inspire and apply new research directions.
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.
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
- Pursue work and research at the intersection of two or more of the following topics: recommender systems, mechanism/market design, multi-agent modeling and optimization, user modeling and simulation, interactive systems, generative AI models, reinforcement learning.
- Design and implement scalable machine learning and optimization techniques to solve problems in user-facing, interactive systems (e.g., recommender systems).
- Pursue a combination of research (with the opportunity to publish) and technology development and innovation in real products.
- Work with other researchers and developers in collaborative teams.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.