Focus on post training data for Large Language Models (LLMs), loss pattern analysis, data quality and impact.

Handle challenging data science problems related to AI models evaluation and training. Utilize AI models and tools as integral components for evaluating, synthesizing, and understanding complex datasets.

Contributes to the design and implementation of novel data acquisition and quality improvement techniques for foundational models.

Contributes to new methodologies to improve the performance of Google's models through better training data, including data acquisition, and insights.

Works cross-functionally with Research, Engineering, and Product teams (e.g., Cloud AI Data and Deep Mind).

Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.

5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.