AI Visual Design Specialist (AI)

TL;DR

AI Visual Design Specialist (Product Design/AI): Train, evaluate, and improve AI-powered creative tools through expert annotation, quality assessment, and design-led thinking with an accent on visual judgment, design fundamentals, and AI system interaction. Focus on developing visual scoring criteria, collaborating cross-functionally with ML engineers and product teams, and prototyping AI-assisted creative workflows.

Location: Beijing, China

Company

hirify.global is a product company specializing in software and AI-driven creative tools.

What you will do

• Annotate and label large volumes of visual data with high-quality tagging related to style, composition, color theory, typography, and visual hierarchy.
• Evaluate AI-generated outputs for accuracy, aesthetic quality, usability, and alignment with design principles and brand standards.
• Develop visual scoring criteria and rubrics to guide model improvement across various creative formats.
• Collaborate closely with machine learning engineers, research scientists, and product teams to provide design-driven feedback loops and translate design concepts into structured feedback.
• Use generative AI tools to create visuals, test hypotheses, prototype user workflows, and explore new AI-assisted creative capabilities.
• Maintain data quality and consistency in annotation projects and contribute to taxonomy development and documentation.

Requirements

• Location: Beijing, China
• Strong grasp of composition, color theory, typography, layout, visual hierarchy, and storytelling principles with a portfolio demonstrating visual design excellence.
• Familiarity with generative AI tools and understanding of AI training data, annotation, and quality metrics.
• Ability to evaluate model output precisely and provide actionable feedback.
• Strong written communication skills and experience collaborating with technical teams.

Nice to have

• Experience with Figma, Adobe Creative Cloud, or 3D tools.
• Prior data labeling, annotation, or ML operations experience.
• Basic familiarity with scripting (Python), prompt engineering, or dataset tooling.
• Knowledge of design accessibility (WCAG), usability heuristics, or user research methods.