Natural Language Processing Research Scientist, Research Full-time

Minimum qualifications:

• PhD degree in Computer Science, with specification in Natural Language Processing, Generative AI, or related fields
• One or more scientific publication submission(s) for conferences, journals, or public repositories.
• Experience coding in any one of these following languages: Python, JavaScript, R, Java, or C .
• Experience in factuality, grounding or evaluation of modern Large Language Models (LLM).

Preferred qualifications:

• 2 years of coding experience in Python, JavaScript, R, Java, or C .
• 1 year of experience owning and initiating research agendas.
• Recent publications at conferences focused on factuality, grounding or evaluation of modern Large Language Models.

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.

One of the requirements from generative models like Gemini is to produce outputs that are consistent with their input context, grounded in real world factual information and offer attribution to support their claims. These needs become more challenging as generative models contexts are longer and more complex. In this role, you will research new modeling approaches for improving the grounding and factuality of Google’s Large Language Models that power prominent Google products such as search Artificial Intelligence (AI) Overviews, Gemini Chat, Cloud Vertex AI and YouTube.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world’s fast-paced business needs.

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 .

Responsibilities

• Author research papers to share and generate impact of research results across the team and in the research community.
• Identify new and upcoming research areas by interacting with potential external and internal collaborators. Develop long-term research strategy and plans to expand the impact of Google research with some guidance.
• Contribute to conducting experiments based on the research question. Develop research prototypes or conduct simulations to further evaluate the impact of research, finalize hypotheses, and refine the research methodology under minimal guidance.
• Perform research for improving Large Language Model (LLM) factuality and grounding capabilities of LLMs.
• Collaborate with other research teams to improve LLM grounding and factuality.