AI Quality Analyst (Personalization) - Hindi
Overview
Turing runs a global evaluation team for Gemini's personalization feature, and this contract role focuses on Hindi responses. You will create multi-turn prompts from your own Google history, including Gmail, Search, YouTube, and past conversations, then rate how well the model uses that context. Scoring centers on Grounding, Integration, and Helpfulness, with side-by-side response comparisons and written justifications. The role requires at least 4 hours per day with PST overlap, up to 40 hours per week, for a 3-month contract.
What You'll Do8
- 1Create and run multi-turn chat prompts (1 to 5 turns) that force the model to draw on your personal Google data and experiences.
- 2Rate each response against your original intent and decide whether the personalization was applied as intended.
- 3Check for Grounding errors by verifying that claims about you are supported by real evidence rather than guesses or hallucinations.
- 4Judge Integration quality by checking if personal data appears in the answer without forced or over-explanatory language.
- 5Compare two model responses side-by-side and rank them based on overall helpfulness, usability, and user enjoyment.
- 6Write concise, structured rationales for each comparison, citing specific turn numbers and exact spots where the model succeeded or failed.
- 7Inspect the model's Debug Info to confirm it used the right chat summaries and data sources.
- 8Delete every evaluation conversation after rating to keep personal history clean and prevent contamination of future sessions.
Requirements11
- 1Read and write Hindi with enough proficiency to evaluate nuanced AI responses in that language.
- 2Use your primary personal Google account and enable personal data sources like Gmail, Search, and YouTube for evaluation.
- 3Maintain full-time availability in your home time zone with at least 4 hours of overlap with PST.
- 4Show strong analytical thinking when judging ambiguous or contradictory AI responses.
- 5Create original, multi-turn prompts based on personal context to stress-test the personalization feature.
- 6Spot personalization failures, such as incorrect inferences or forced connections between user data and the answer.
- 7Compare side-by-side model responses and catch small differences in naturalness and overnarrating.
- 8Write clear rationales that reference specific turn numbers and evidence from the conversation.
- 9Work on your own and stay organized in a remote setting.
- 10Hold a BS/BA degree or equivalent experience in a field like Linguistics, Journalism, Computer Science, or a related analytical discipline.
- 11Bring prior experience in data annotation, AI quality evaluation, or content moderation (preferred).
Who Should Apply
The ideal candidate is a fluent Hindi speaker who enjoys dissecting how AI uses personal data to shape answers. This person should be comfortable turning their own Gmail, Search, YouTube, and chat history into test prompts and then judging the results with written evidence. The role suits someone who can commit 4 hours daily with PST overlap for a 3-month contract and who treats data privacy with care. People who dislike sharing personal Google data or who prefer fixed, repetitive tasks will find this role less suitable. Candidates often get rejected when they fail the written assessment within 24 hours or when their rationales lack specific turn references.
Salary Insight
The project pays $15 per hour and runs for 3 months as a contractor engagement.
Location
Required Skills
Application Tip
Before you apply, write a sample SxS evaluation for two AI responses and reference the exact turn numbers where each response succeeded or failed. The screening assessment will test whether you can justify rankings with concrete evidence.
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