Frontend Engineer — Web Replication Preference Rater

About the work

We're building a high-quality dataset of human preference judgments on AI-generated frontend code. You'll be shown a reference web page alongside two candidate replications produced by AI models, and you'll decide which replication is better — then explain why in writing that a model can learn from.

This is evaluation work, not authoring. You won't be building sites from scratch. You'll be reading someone else's HTML and CSS, running it locally, comparing it pixel-by-pixel against a target, and articulating exactly where and why it falls short.

What you'll do

• Render a reference page and two candidate replications side by side at desktop width and judge which is the closer reproduction.

• Diff layout 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.

• Inspect the underlying markup with browser devtools to distinguish a replication that is genuinely correct from one that merely looks correct at one viewport — hardcoded pixel offsets, absolute positioning standing in for real layout, and inline styles that will not survive a resize.

• Evaluate responsive behavior and semantic quality: whether flexbox and grid are used where they belong, whether legacy float or table layouts in the reference were reproduced faithfully, whether headings and landmarks carry real semantic meaning.

• Write a structured rationale for every judgment — the specific defects you found, ranked by how much they matter, in language precise enough to be actionable.

• Flag ties, ambiguous cases, and broken task items rather than forcing a preference.

You're a fit if you have

• 3+ years of professional web development experience, primarily in frontend or full-stack work.

• Fluency in hand-written HTML and CSS: semantic markup, flexbox, grid, media queries, and older float- and table-based layouts you can still read and reason about.

• Working command of browser devtools — element inspection, computed styles, the box model, and the network panel.

• Enough JavaScript to read a page's scripts and understand what they do to the DOM, even if you don't write JS daily.

• Comfort in a terminal: cloning a folder and serving it over a local static server without help.

• Strong written English and the discipline to justify a judgment rather than assert it.

Equipment

• A desktop or laptop with a browser window that opens to at least 1920px wide.

• Administrator rights on your own machine, so you can install and run a local server.

Nice to have

• Prior RLHF, preference labeling, or model evaluation work.

• A code review or technical assessment background.

• Pixel-perfect design-to-code experience — translating Figma or PSD comps into production markup.

• Web accessibility expertise (WCAG, ARIA, screen reader testing).

• Familiarity with how LLMs typically fail at codegen.

• Web scraping or DOM parsing experience.

Note: this seat is for practicing web developers. Backend-only, mobile-native-only, data science, DevOps, and design-without-code backgrounds are out of scope for this project.

We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request.

Contract and Payment Terms

• You will be engaged as an independent contractor.
• This is a fully remote role that can be completed on your own schedule.
• Projects can be extended, shortened, or concluded early depending on needs and performance.
• Your work at Mercor will not involve access to confidential or proprietary information from any employer, client, or institution.
• Payments are weekly on Stripe or Wise based on services rendered.
• Please note: We are unable to support H1-B or STEM OPT candidates at this time.

About Mercor

Mercor partners with leading AI labs and enterprises to train frontier models using human expertise. You will work on projects that focus on training and enhancing AI systems. You will be paid competitively, collaborate with leading researchers, and help shape the next generation of AI systems in your area of expertise.