Domain Expert Lead- STEM (Contract), AGI - Data Services

Amazon•Boston, MA

10h

About The Position

Embark on a transformative journey as our Domain Expert Lead, where intellectual rigor meets cutting-edge technological innovation. In this pivotal role, you will serve as a strategic architect of data integrity, leveraging your domain expertise to advance AI model training and evaluation. Your domain knowledge and experience will be instrumental in elevating our artificial intelligence capabilities, meticulously refining data collection processes and ensuring the highest standards of quality and precision across complex computational landscapes.

Requirements

1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)

Nice To Haves

Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)
Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R
Knowledge of machine learning concepts and their application to reasoning and problem-solving
Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)
Experience working with or evaluating AI systems
Experience applying quantitative analysis to solve business problems and making data-driven business decisions
Experience effectively communicating complex concepts through written and verbal communication

Responsibilities

Critically analyze and evaluate responses generated by our LLMs across various domains and use cases in your area of expertise.
Develop and write demonstrations to illustrate "what good data looks like" in terms of meeting benchmarks for quality and efficiency
Participate in the creation of tooling that helps create such data by providing your feedback on what works and what doesn’t.
Champion effective knowledge-sharing initiatives by translating domain expertise into actionable insights, while cultivating strategic partnerships across multidisciplinary teams.
Provide detailed feedback and explanations for your evaluations, helping to refine and improve the LLM's understanding and output
Collaborate with the AI research team to identify areas for improvement in the LLM’s capabilities
Stay abreast of the latest developments in how LLMs and GenAI can be applied to your area of expertise to ensure our evaluations remain cutting-edge.