Research Scientist, Gemini Factuality, DeepMind

Google DeepMind; Mountain View (CA); On-site; USD 174,000 - 253,000; Full time

Job summary

Google DeepMind is seeking a Research Scientist to improve the factuality of the Gemini model family and bridge the gap between research and production. You will design advanced training methodologies to reduce hallucinations and build automated evaluation systems to measure the model's accuracy across real-world knowledge domains.

Google DeepMind values safety and ethics, with global teams delivering impact for billions of users and opportunities to influence research directions and product

Qualifications

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.

Responsibilities

• Develop evaluation methods for detecting factual inaccuracies in all LLM generated content.
• Design and implement advanced pre-training, supervised fine tuning (SFT), and reinforcement learning strategies to maximize the generation of factual content.
• Innovate on algorithmic interventions and data curation strategies to improve model calibration, ensuring Gemini accurately identifies its own knowledge boundaries.

Skills

Programming

Research leadership

Influence researchers

Education

PhD in Computer Science or related field

Tools

Coding

Job description

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.

Minimum qualifications

• PhD in Computer Science, a related field, or equivalent practical experience.
• 2 years of experience leading a research agenda.

Preferred qualifications

• 2 years of coding experience.
• 1 year of experience leading research efforts and influencing other researchers.

About The Job

As a Research Scientist, you will be responsible for improving the factuality of the Gemini model family. You will bridge the gap between research and production. You will also design advanced training methodologies to reduce hallucinations and build automated evaluation systems to measure the model's accuracy across real-world knowledge domains.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $253000 (USD) + 15% bonus target + equity + benefits

Responsibilities

Learn more about benefits at Google .

• Develop evaluation methods for detecting factual inaccuracies in all LLM generated content.
• Design and implement advanced pre-training, supervised fine tuning (SFT), and reinforcement learning strategies to maximize the generation of factual content.
• Innovate on algorithmic interventions and data curation strategies to improve model calibration, ensuring Gemini accurately identifies its own knowledge boundaries.

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 .