Imagine being at the core of the AI revolution, where your expertise directly fuels the most advanced Large Language Models. We are the driving team behind high-quality data – the essential ingredient for unlocking unprecedented AI breakthroughs. Partner with the most resourceful minds, define data excellence, and make a tangible impact on the future of intelligent systems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google .
• Be a distinct contributor, with a particular focus on Human Data Collection for Large Language Models (LLMs) and address complex data science problems.
• Design and deploy novel data acquisition and quality improvement techniques for foundational models.
• Utilize AI models and tools as integral components for evaluating, synthesizing, and understanding complex datasets.
• Act as a critical technical partner, collaborating closely with Research, Engineering, and Product teams (Cloud AI Data and Google DeepMind).
• Develop new methodologies to improve the performance of Google's models through better training data, including data collection, and insights.
• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree.
Minimum qualifications:
• Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
• 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree.
Preferred qualifications:
• 10 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of experience with a PhD degree.