AI Quality Analyst - Chinese

Turing

6d•$15•Remote

About The Position

As an AI Quality Analyst, you will evaluate a new personalization feature for Gemini. You will assess how well the model uses information from your past Gemini conversations, Gmail, Google Search, and YouTube activity to make responses more relevant and helpful. This role requires a unique blend of creativity and analytical rigor. You will actively design prompts from the perspective of your own personal experiences. You will then use your analytical skills to assess the quality of the model's personalized responses, evaluating dimensions like Grounding, Integration, and Helpfulness.

Requirements

Ability to read and write in Chinese with a high degree of comp, as Chinese is the focus language for this project.
Experience in designing creative, multi-turn starting prompts based on personal context to thoroughly test the model's capabilities.
Understanding of personalization concepts, including the ability to identify incorrect personalization, poor inferences, and forced connections.
The ability to review Side-by-Side (SxS) model responses and spot subtle differences in naturalness and overnarrating.
Superior ability to write clear, concise, and structured rationales for model rankings, explicitly referencing specific turn numbers.
Ability to provide constructive feedback and detailed annotations.
BS/BA degree or equivalent experience in a relevant field (e.g., Policy, Law, Ethics, Linguistics, Journalism, Computer Science, or a related analytical field).

Nice To Haves

Experience in data annotation, AI quality evaluation, content moderation, or a related role is strongly preferred.

Responsibilities

Designing and executing multi-turn conversational prompts (typically 1-5 turns) that require the AI to utilize your personal information and experiences.
Analyzing responses for Grounding issues, ensuring claims about you are supported by evidence and not flawed inferences or hallucinations.
Rigorously evaluating and stack-ranking two model responses side-by-side (SxS) to determine which is overall more helpful, easy to use, and enjoyable.
Writing clear, defensible rationales for your comparisons, explicitly referencing where issues or positive aspects occurred in the conversation.
Extracting and verifying "Debug Info" from the model to confirm that chat summaries and data sources were properly utilized.
Maintaining strict data hygiene by deleting evaluation conversations to prevent them from polluting your future chat history.