You will review AI-generated HTML/CSS code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards.

You will assess work for semantic correctness, visual layout logic, accessibility, responsive design, browser compatibility, CSS architecture, maintainability, performance, formatting, instruction-following, and adherence to project-specific rubrics. This role requires strong frontend markup and styling expertise, English communication skills, excellent attention to detail, and the ability to manage quality workflows across remote technical teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your HTML/CSS quality leadership will help ensure frontend training data is accurate, accessible, responsive, clearly explained, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important:

There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

• Quality monitoring: Spot-check HTML/CSS items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues.
• Code review: Evaluate AI-generated HTML/CSS snippets, layout implementations, accessibility fixes, responsive design solutions, debugging responses, and explanations for correctness and clarity.
• Trainer and QA communication: Update contributors on Discord about guideline changes, workflow updates, and HTML/CSS-specific review standards.
• Question handling: Respond to questions around semantic HTML, accessibility, ARIA, CSS specificity, layout behavior, flexbox/grid, responsive design, browser compatibility, and rubric interpretation.
• Trainer/QA activation management: DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.
• Documentation: Create and maintain HTML/CSS style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials.
• Onboarding and training: Run onboarding/training calls for HTML/CSS contributors.
• Risk and accessibility review: Flag inaccessible, misleading, invalid, brittle, or non-production-ready frontend recommendations.
• Process improvement: Identify recurring quality gaps and build scalable QA processes.

• Bachelor’s or Master’s degree in Computer Science, Web Development, UX/UI, Information Technology, or equivalent professional frontend development experience.
• Strong grasp of English to follow guidelines, communicate with teams, and provide clear technical feedback.
• 3+ years of professional experience in HTML/CSS, frontend development, web accessibility, responsive design, UI implementation, code review, QA, or technical mentoring.
• Strong understanding of semantic HTML, forms, tables, ARIA basics, accessibility, CSS selectors, cascade/specificity, box model, flexbox, grid, positioning, responsive layouts, media queries, animations, and modern CSS features.
• Ability to evaluate HTML/CSS content against detailed rubrics and identify issues such as invalid markup, inaccessible components, poor responsiveness, layout bugs, overcomplicated CSS, specificity problems, browser compatibility issues, or incomplete explanations.
• Familiarity with tools and workflows such as browser DevTools, Lighthouse, WCAG basics, Sass, Tailwind CSS, Bootstrap, CSS modules, design systems, Figma handoff, GitHub, CI/CD, and frontend build tools is preferred.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, frontend engineers, designers, coding mentors, or QAs is strongly preferred.
• Comfortable working in fast-moving remote environments using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems.
• Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation.
• Experience with AI training, data annotation, LLM evaluation, frontend code QA, accessibility review, or rubric-based code review is a strong plus.

Interview required.

Work arrangement: Fully remote

Eligible countries: United States