Mercor · General projects
Applied Engineer, Evaluations Role
Listed on Mercor as “Applied Engineer, Evaluations Role”
How this rate compares
This listing
$100–$120 per hour
Typical in General projects
$55–$70 per hour
Above the typical range
Typical: the middle of the lowest and highest rates posted by 119 listings in this category on Seoulstart, in US dollars.
What this actually is
You complete short labeling tasks, record everyday activities, or evaluate AI outputs across general knowledge domains. Open to most backgrounds. The platform title (Applied Engineer, Evaluations Role) reflects the rate band and the expertise required, not the day-to-day work.
How Mercor picks people
- Upload your CV and answer the role's written questions.
- Do a video interview with Mercor's AI interviewer. Most take about 20 minutes, in English unless the role says otherwise.
- Some roles add a skills test. A test you pass once counts for similar roles.
- The project team reviews your results and sends offers to the people it picks.
Before you start
- Take Mercor's free practice interview first. It does not count toward any application.
- Use Chrome on a computer with a camera and microphone, in a quiet room.
- You can retake an official interview up to 3 times, but hiring teams see how many times you retook it.
Not every applicant gets an offer. Prepare well for the interview.
How to prepare for the Mercor interview
Source: Mercor's help pages. talent.docs.mercor.com
Can you do this on your visa?
F-2 / F-4 / F-5 / F-6: open. E-1 to E-7: needs concurrent-employment permit. D-2 / D-4 students: S-3 permit, 20 hr/week cap. D-10 / D-8: case by case.
Korean tax on USD income
First 5 years in Korea: foreign-source income only taxed if remitted into Korea. After year 5: worldwide income. Full tax guide.
Original posting from Mercor
Mercor is seeking software engineers to build and refine evaluations. You’ll turn completed pull requests into engineering tasks and use our in-house evaluation framework to multiple frontier coding agents, including Claude Code, Codex and more.
We work alongside an in-house research team and have produced industry leading benchmarks to compare the performance of frontier large language models.
In this role, you will:
- Identify repositories with enough substantive work to support challenging evaluations, and select suitable completed PRs.
- Investigate each problem, its reference solution, and the repository’s architecture, tests, and conventions.
- Write task prompts and build evaluations using automated tests, shell commands, and LLM grading prompts.
- Validate evaluations against reference solutions and deliberately flawed implementations. Find missing checks, incorrect grades, and criteria that unnecessarily constrain how a problem can be solved.
- Run evaluations repeatedly across multiple models and harnesses. Investigate whether failures come from the agent’s solution, the environment, or the grading, and establish that tasks expose meaningful weaknesses in agent performance.
- Refine evaluations through repeated testing and review. Document findings and grading decisions, and work through feedback.
You’ll need:
- Strong programming fundamentals and practical experience working in substantial and complex codebases. Languages we create evals for include TypeScript/JavaScript, Python, Java, Kotlin, Go, Ruby, PHP, C++ and Rust
- The ability to understand unfamiliar code, investigate subtle behavior, and assess whether different implementations solve the same problem correctly.
- Experience writing meaningful tests, including edge cases and regression coverage.
- Attention to detail and patience for repeated investigation and refinement.
- Practical experience using AI coding tools, with the judgment to verify their output and catch mistakes.
- Confidence using Git, test runners, and CI tooling.
- Clear and fluent written and verbal communication with the ability to own a task independently while raising questions when requirements are ambiguous.
Relevant experience can come from open-source, private, or enterprise repositories. Familiarity with a particular language or ecosystem is helpful; the ability to learn the repository and make sound engineering judgments matters more than its popularity or your public contribution history.
We provide onboarding to the evaluation framework and ongoing review feedback. After onboarding, you’ll be expected to own task selection, evaluation development, and iteration without step-by-step direction.
Quoted from Mercor's public listing on 2026-11-13. We don't edit platform copy; honest framing is in the title and the “what this actually is” block above.
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About Mercor
AI-interview-based talent network. One application, voice interview with their AI, then matched to projects across coding, research, and specialist work. Pay scales with track and seniority.
Mercor review: AI-interview talent network
4.1/5 on Glassdoor, fastest-growing platform in the category (+509% YoY). What the AI video interview actually asks, real pay across coding/research/medical/legal/finance tracks ($25-$200/hr), and the project-availability problem.
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