Data Annotation Analyst (Turkish) | $11/hr Remote

Position: LLM AI Quality Analyst (Personalization) Turkish Type: Contract Compensation: $11/Hour Location: Remote Commitment: Full-time (8 hours/day) | Short-Term Contract (2 months) Role Responsibilities Evaluate and assess AI-generated responses with a focus on personalization quality and user relevance Analyze nuanced and ambiguous outputs to ensure alignment with project standards and expectations Review, annotate, and provide feedback on AI model behavior and response quality Perform quality assurance tasks related to large language model outputs and personalization workflows Collaborate with internal teams to improve AI training data and evaluation processes Ensure accuracy, consistency, and compliance with project guidelines Complete assigned tasks within required timelines and productivity expectations Requirements Turkish proficiency with the ability to read and write in Turkish at a high level of comprehension Experience in data annotation, AI quality evaluation, content moderation, or a related field is strongly preferred Strong analytical thinking and attention to detail Ability to evaluate complex and ambiguous AI-generated responses BS/BA degree or equivalent experience in a relevant field such as Policy, Law, Ethics, Linguistics, Journalism, Computer Science, or a related analytical discipline Willingness to use a primary personal Google account and enable personal data sources for project evaluation purposes Full-time availability in the local time zone with a minimum 4-hour overlap with PST time zone Ability to follow instructions and work effectively in a fast-paced environment Preferred Qualifications Previous experience working on AI personalization or LLM evaluation projects Familiarity with annotation platforms and quality review workflows Strong written communication and critical thinking skills Experience working in global operations or remote project environments Application Process Apply via Apply/Easy Apply and complete the required assessment Shortlisted candidates will undergo an evaluation process Selected candidates will be contacted by the team regarding next steps