Mercor · Finance & specialist

ML Challenge Task Auditor

Listed on Mercor as “ML Challenge Task Auditor”

$70-$90/hrRemoteContractPaid in USD

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How this rate compares

This listing

$70–$90 per hour

Typical in Finance & specialist

$60–$100 per hour

Within the typical range

Typical: the middle of the lowest and highest rates posted by 345 listings in this category on Seoulstart, in US dollars.

What this actually is

You bring your specialist expertise to AI evaluation. The shape of the work varies but the pattern is the same: review outputs, rate quality, write prompts, flag errors. The platform title (ML Challenge Task Auditor) 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

Evaluate the quality, correctness, and methodological rigor of applied machine-learning tasks used to train and evaluate a frontier AI lab's models. You'll assess experiment design, model-selection reasoning, and evaluation methodology - and provide clear, rubric-based written feedback.

Basic Qualifications

• 3+ years hands-on applied/experimental ML (experiment design, model selection, hyperparameter tuning, evaluation methodology)

• Strong grasp of data-quality rigor: leakage detection, metric gaming, and train/test/CV hygiene

• Proficiency with standard ML frameworks (PyTorch, TensorFlow, scikit-learn, XGBoost)

• Ability to critique ML claims against evidence and reproduce results

Preferred Qualifications

• Competition / benchmark experience (e.g., Kaggle)

• Graduate research or publication record in applied ML

• Prior task-grading or peer-review experience

Note: this role evaluates applied/experimental ML rigor - it is not an LLM-application-building or MLOps role.

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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