I am looking for an AI-native visual designer to join a global tech client who specialise in online design and publishing.
The ideal candidate for this role is curious about the future of AI-driven creativity and to influence how AI models see and create. You must have the ability to direct AI from a creative perspective and have experience in prompt engineering.
Start Date: Ideally Asap
Duration: 3 month contract with the possibility to extend to 6 months.
IR35 Status: Inside IR35 (must go through an Umbrella company
Location: Fully remote open to both UK and South Africa based candidates.
UK Day Rate: Depending on exp rate will range from £350-£480. (SA rate TBC)
Summary:
An AI-Native Visual Designer becomes the bridge between design excellence and model research. In a Core Research environment, the designer materially strengthens the feedback loops needed to push models toward world-class performance. This designer ensures the client's visual AI is trained, evaluated, and improved using world class design judgment: accelerating Research’s ability to ship models that feel premium, intuitive, and globally competitive.
• They bring human visual judgment into model training
• They create high-quality, high-granularity annotation data
• They strengthen the human-in-the-loop evaluation cycle
• They translate research improvements into designer-centric feedback
• They bring a user-centered lens to foundational research
Key Responsibilities:
Visual Evaluation & Annotation
• Annotate and label large volumes of visual data (images, UI layouts, compositions, graphics, photos).
• Provide high-quality tagging related to style, composition, color theory, typography, and visual hierarchy.
• Evaluate AI-generated output for accuracy, aesthetic quality, usability, and alignment with design principles.
• Identify patterns, errors, and edge cases to improve model performance
Design Quality Assessment
• Develop visual scoring criteria and rubrics to guide model improvement.
• Review outputs across various creative formats (illustration, branding, UI components, marketing visuals).
• Validate whether outputs meet user expectations, brand standards, accessibility guidelines, and ethical guidelines.
Cross-Functional Collaboration
• Work closely with machine learning engineers, research scientists, and product teams to provide design-driven feedback loops.
• Translate design concepts into structured feedback that model teams can use (e.g., style attributes, visual defects, composition rules).
• Help communicate creative insights into technical documentation.
Prototyping & Creative Exploration
• Use generative AI tools to create visuals, test hypotheses, and prototype user workflows.
• Explore new capabilities and push the boundaries of AI-assisted creativity.
• Offer creative direction for improving model outputs and user-facing features.
Data & Process
• Maintain data quality and consistency in annotation projects.
• Contribute to the development of taxonomies for visual styles, attributes, and design patterns
• Document annotation methodologies and participate in improving annotation tooling
Experience and Skillset
Design Foundations
• Strong grasp of composition, colour theory, typography, layout, visual hierarchy, and storytelling principles.
• Portfolio demonstrating visual design excellence across one or more domains (graphic, product, UI/UX, illustration, etc.)
AI & Technical Understanding
• Familiarity with generative AI tools (image models, large language models, design AIs).
• Understanding of how AI training data, annotation, and quality metrics influence model behavior.
• Ability to evaluate model output with precision and articulate actionable feedback.
Collaboration & Communication
• Able to translate design critique into structured, repeatable feedback for technical and product partners.
• Experience collaborating with engineers, researchers, or technical teams is a plus.
• Strong written communication skills and comfort in documentation-heavy workflows.
Bonus Skills
• Experience with Figma, Adobe Creative Cloud, or 3D tools.
• Prior data labelling, 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.
Please apply with your CV and portfolio.