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Frontend Code Evaluation Specialist - AI Trainer

Job Description - Frontend Code Evaluation Specialist - AI Trainer

About the job

Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark, General Catalyst, Peter Thiel, Adam D'Angelo, Larry Summers, and Jack Dorsey.

Position: Frontend Engineer
Type: Contract
Compensation: $90/hour
Location: Remote

Role Responsibilities

  • Render a reference page and two candidate replications at 1920×1080. Judge which is the closer reproduction, state by state.
  • Diff visual fidelity in detail: box model and spacing, typography (family, size, weight, line-height, letter-spacing), color and border treatment, image and asset handling, z-order, and overflow.
  • Read the source of both attempts and grade construction quality. Distinguish a replication that is genuinely correct from one that merely looks correct at one viewport.
  • Test responsiveness. Identify defects such as a nav bar that looks right at 1920px but collapses at 1400px.
  • Write specific, evidence-cited justifications for every preference. Provide detailed explanations like "B nests the article body in a single absolutely-positioned div, so the text overlaps the footer below 1600px, while A uses normal document flow."
  • Use the "this task is broken" escape hatch with judgment. Distinguish a task that genuinely cannot be completed from one that is merely hard.

Qualifications

Must-Have

  • 3–8 years of professional web development experience in frontend or full-stack work.
  • Fluency across web eras, including legacy layouts like used for layout.
  • Command of hand-written HTML and CSS: semantic markup, flexbox, grid, media queries, and legacy float- and table-based layouts.
  • Browser DevTools as muscle memory.
  • Command-line comfort: unzipping an archive, standing up a static local server, and untangling a broken image reference.
  • Enough JavaScript to read a page's scripts and understand their DOM impact.
  • Professional written English for task justification.

Preferred

  • Prior RLHF, preference-labeling, model-evaluation, or structured code-review work.
  • Pixel-perfect design-to-code experience.
  • Accessibility expertise (ARIA, semantic landmarks, heading hierarchy).
  • Familiarity with how LLMs fail at code generation.
  • Web scraping, archiving, or DOM-parsing background.
  • More than one completed Mercor project and availability in contiguous multi-hour blocks.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: [email protected]

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.



#hiringmercor
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