Generative AI Analyst - Chinese

Welocalize • San Francisco, CA

1d • Onsite

About The Position

We are hiring onsite Generative AI Analysts in San Jose, CA to perform annotation efforts of Chinese (zh-CN) multimedia and language data labeling and review work (e.g., video, images, and related metadata). This role focuses on annotation, data quality, prompt evaluation, and the creation of high-quality datasets used to train and improve generative AI models.

Requirements

• Native level proficiency in Chinese (zh-CN) and English with excellent written and verbal communication skills.
• Strong attention to detail and ability to follow complex annotation guidelines
• Interest in generative AI, machine learning, and emerging AI technologies
• Ability to be onsite at client headquarters (San Jose, CA) full time.
• Bachelor’s degree or equivalent practical experience

Nice To Haves

• Experience with data annotation, content evaluation, labeling operations, or quality review workflows preferred
• Domain expertise in Finance, STEM, Legal, Medical, Coding, or other specialized fields is a plus
• Familiarity with generative AI systems, large language models, RLHF, or multimodal AI workflows
• Domain knowledge in Law/Medical/Math/Coding/etc.
• Bilingual proficiency preferred (Korean, Japanese, Mandarin, Spanish, German, or French)
• Experience annotating prompts, responses, images, video sequences, or other AI training data
• QA/testing experience within AI, data operations, or content review environments
• Experience working with evaluation rubrics, taxonomy development, or dataset quality initiatives
• Python or scripting experience is a plus

Responsibilities

• Perform annotation and labeling tasks for Chinese language (zh-CN) generative AI datasets, including text, image, video, and multimodal content
• Create, review, and evaluate prompts and responses across a variety of domains and use cases
• Conduct quality assurance reviews to ensure annotation accuracy, consistency, and adherence to guidelines
• Assist in developing and refining annotation guidelines and evaluation criteria
• Support data collection, categorization, tagging, and evaluation workflows for machine learning systems
• Identify edge cases, inconsistencies, and quality issues within datasets and model outputs
• Collaborate with internal teams and external partners to improve annotation quality and operational efficiency
• Provide feedback on workflows, tooling, and annotation processes

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level