Senior Research Scientist, Conversational and Agentic Systems, Google Research

Google•Mountain View, CA

4d•$174,000 - $252,000

About The Position

As a Research Scientist at Google, you will conduct research on user-facing conversational and agentic systems. You will develop novel modeling and algorithmic techniques to advance the design and deployment of interactive systems, with work in areas such as user modeling and simulation, multi-turn optimization and reinforcement learning, agent and multiagent architectures, and recommender systems. You will collaborate with Researchers, Software Engineers, Research Software Engineers, and Product Managers to translate research and prototypes into robust, scalable, production-ready AI systems. Google Research maintains a portfolio of projects spanning fundamental research, product innovation, product contribution, and infrastructure goals. Research Scientists set up large-scale tests, deploy promising ideas, manage deadlines and deliverables, and apply current theories to develop products, processes, and technologies. They create experiments and prototypes, design architectures, and work on real-world problems across computer science. They also contribute to the wider research community by sharing and publishing findings, including work inspired by internal projects and collaborations with universities and technical institutes. The role partners with Search, Cloud, YouTube, and other product teams to help move projects from theory or proof of concept into product applications. Individual pay is determined by job-related skills, experience, and relevant education or training. The stated US compensation is $174,000–$252,000, plus a 15% bonus target, equity, and benefits.

Requirements

PhD in Computer Science, a related field, or equivalent practical experience.
At least 2 years of experience leading a research agenda.
One or more scientific publication submissions to conferences, journals, or public repositories, such as CVPR, ICCV, NeurIPS, ICML, or ICLR.

Nice To Haves

PhD in Machine Learning, Artificial Intelligence, or another related field, or equivalent practical experience.
At least 3 years of experience with research agendas spanning multiple teams or projects.
At least 2 years of coding experience.
Research and practical experience in one or more of reinforcement learning, planning in agentic systems, foundation models, or user modeling.
Track record of contributing to research communities or efforts, including regularly publishing papers at conferences.
Strong communication skills.

Responsibilities

Help grow the research business by sharing research trends and best practices within the community.
Drive project work by defining data structures, frameworks, designs, and evaluation metrics for research solution development and implementation; identify timelines and obtain needed resources.
Collaborate with Researchers, Engineers, and Product Managers to identify problems or gaps in existing technology and engage stakeholders and leaders to address them.
Conduct research at the intersection of user-facing conversational and agentic systems, user modeling, and multi-turn optimization.
Partner with Search, Cloud, YouTube, and other product teams to move projects from theory or proof of concept to product applications.