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M

Md Danish Imam

Senior UX/UI Designer

INDIA flag
Delhi, India
$30.00/hrIntermediateLabel StudioInternal Proprietary Tooling

Key Skills

Software

Label StudioLabel Studio
Internal/Proprietary Tooling

Top Subject Matter

Design Industry

Top Data Types

Computer Code ProgrammingComputer Code Programming

Top Task Types

Evaluation Rating

Freelancer Overview

Senior UX/UI Designer. Brings 10+ years of professional experience across complex professional workflows, research, and quality-focused execution. Currently contributing to AI design model training by evaluating and labeling AI-generated visual outputs using Label Studio. My work involves assessing layouts against design rubrics — including usability, visual hierarchy, and human-centric aesthetics — to help fine-tune AI systems for better user acceptance and accuracy. - Apply advanced rubric-based evaluation to assess AI-generated visual designs for usability, hierarchy, and aesthetic accuracy. - Deliver consistent, high-quality annotations that guide AI systems to replicate human-level design judgment. - Coordinate directly with AI engineers and product teams to improve model performance and evaluation standards. Education includes Bachelor of Technology, Maulana Azad College of Engineering & Technology (Magadh University) (2012).

IntermediateEnglish

Labeling Experience

AI Design Curator

ImageEvaluation Rating
Contributing to the development and optimization of AI-powered design models by evaluating and labeling AI-generated visual outputs. The project focuses on improving model performance in UI/UX design understanding, ensuring outputs align with human-centered design principles, usability standards, and real-world design expectations. Data Labeling Tasks Performed Conduct rubric-based evaluation of AI-generated UI layouts using predefined criteria such as: Usability & accessibility Visual hierarchy & spacing Alignment and consistency Aesthetic quality and design coherence Annotate outputs using Label Studio, providing: Structured ratings (quantitative scoring) Detailed qualitative feedback for model improvement Identify design flaws such as: Poor navigation flow Inconsistent typography or spacing Misaligned components or weak visual hierarchy Compare multiple AI-generated variations and select the best-performing design based on human UX judgment Project Size & Scale Evaluated and annotated hundreds to thousands of design samples across multiple UI categories (e.g., dashboards, onboarding flows, mobile interfaces) Worked in iterative training cycles, contributing to continuous model refinement Collaborated in a cross-functional environment with AI engineers, product managers, and design researchers Quality Measures & Standards Maintained high annotation consistency by strictly adhering to defined evaluation rubrics and guidelines Followed inter-annotator agreement practices to ensure reliability and reduce subjectivity Performed self-audits and peer reviews to validate annotation accuracy Ensured low error rates and high precision in labeling to directly impact model performance Provided actionable feedback loops to improve both annotation guidelines and AI output quality Impact Helped improve AI model’s ability to generate user-friendly and aesthetically accurate UI designs Enabled systems to better replicate human design judgment and decision-making Contributed to enhancing end-user acceptance and usability of AI-generated interfaces

Contributing to the development and optimization of AI-powered design models by evaluating and labeling AI-generated visual outputs. The project focuses on improving model performance in UI/UX design understanding, ensuring outputs align with human-centered design principles, usability standards, and real-world design expectations. Data Labeling Tasks Performed Conduct rubric-based evaluation of AI-generated UI layouts using predefined criteria such as: Usability & accessibility Visual hierarchy & spacing Alignment and consistency Aesthetic quality and design coherence Annotate outputs using Label Studio, providing: Structured ratings (quantitative scoring) Detailed qualitative feedback for model improvement Identify design flaws such as: Poor navigation flow Inconsistent typography or spacing Misaligned components or weak visual hierarchy Compare multiple AI-generated variations and select the best-performing design based on human UX judgment Project Size & Scale Evaluated and annotated hundreds to thousands of design samples across multiple UI categories (e.g., dashboards, onboarding flows, mobile interfaces) Worked in iterative training cycles, contributing to continuous model refinement Collaborated in a cross-functional environment with AI engineers, product managers, and design researchers Quality Measures & Standards Maintained high annotation consistency by strictly adhering to defined evaluation rubrics and guidelines Followed inter-annotator agreement practices to ensure reliability and reduce subjectivity Performed self-audits and peer reviews to validate annotation accuracy Ensured low error rates and high precision in labeling to directly impact model performance Provided actionable feedback loops to improve both annotation guidelines and AI output quality Impact Helped improve AI model’s ability to generate user-friendly and aesthetically accurate UI designs Enabled systems to better replicate human design judgment and decision-making Contributed to enhancing end-user acceptance and usability of AI-generated interfaces

2025 - Present

Education

M

Maulana Azad College of Engineering & Technology (Magadh University)

Bachelor of Technology, Computer Science Engineering

Bachelor of Technology
2008 - 2012

Work History

F

Freelance

AI Design Curator

Delhi
2025 - Present
R

Roboquess Infotech Private Limited

Senior UX/UI Designer

Delhi
2025 - Present