Minimum qualifications:

• PhD degree in Computer Science, a related field, or equivalent practical experience.
  
• 4 years of experience with research agendas across multiple teams or projects.
  
• One or more scientific publication submissions for conferences, journals, or public repositories.
  
• 
  Experience in Natural Language Processing, Machine Learning, or Large Language Models.
  
  

Preferred qualifications:

• 2 years of experience in coding and leading multiple research efforts and influencing research direction.
  
• Experience in the medical domain.
  
• 
  Experiences with Large Language Model Development.
  
  

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.

Google Health is a company-wide effort to help billions of people be healthier. We work toward this vision by meeting people in their everyday moments and empowering them to stay healthy and partnering with care teams to provide more accurate, accessible, and equitable care. Our teams are applying our expertise and technology to improve health outcomes globally - with high-quality information and tools to help people manage their health and wellbeing, solutions to transform care delivery, research to catalyze the use of artificial intelligence for the screening and diagnosis of disease, and data and insights to the public health community.

The US base salary range for this full-time position is $189,000-$284,000 + 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

• Work with a team to improve healthcare.
  
• Manage data analysis/curation, developing the necessary infrastructure to do research, performing experiments, and detailed evaluations from a research or product perspective, collaborate with onsite clinicians, product managers, and other research/engineering teams in Google Research, and partner teams in Search, YouTube, and Gemini.
  
• Develop and improve AI models on challenging health-related tasks, such as grounding and medical factuality, automated clinical evaluations, video/audio understanding, multi-turn discussions on consumer health topics, and more.
  
• Build and improve AI research infrastructure by ingesting new datasets, collecting and analyzing quality data, and maintaining training and evaluation infrastructure.
  
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  Perform research on health-related problems, with potential to publish externally.