Research Scientist, Interactive Recommender Systems, Research

Minimum qualifications:

• PhD in Computer Science, a related field, or equivalent practical experience.
• One or more scientific publication submission(s) for conferences, journals, or public repositories.
• Experience with one or more of the following: multi-agent systems, algorithmic mechanisms or market design, recommender systems, reinforcement learning or active learning, generative AI.

• 2 years of coding experience.
• 1 year of experience owning and initiating research agendas.
• Experience with Machine Learning methods.
• Experience programming in C, C++, or Python.
• Experience with publication record.

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 team is focused on research to develop the next generation of technologies to power systems such a recommenders and other user-facing products at Google, with an emphasis on long-term user satisfaction.

The US base salary range for this full-time position is $136,000-$200,000 + 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.

• Work with and research two or more of the following topics: recommender systems, mechanism/market design, multi-agent modeling and optimization, user modeling, interactive systems, generative AI models, reinforcement learning.
• Design and implement scalable machine learning and optimization techniques to solve real-time 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.