Machine Learning Expert
The research teams behind the best-known AI models come to Mercor for machine learning judgment they can't generate on their own. Your standards and expertise become the rubric that frontier AI is graded against.
Hiring companyMercor
About the role
This is a standing listing for machine learning practitioners who want AI training and evaluation work, not a specific job opening. It stays open whether or not a matching project is running this week.
New projects start on short notice, so instead of posting and pulling a listing each time, we keep one open per field and draw from it when one begins.
We match machine learning practitioners in the network to projects like:
Where you trained matters less than whether you have put models in front of real users and dealt with what came back.
How it works
Apply here with your resume and confirm where you work from, then take a short AI interview, about 20 minutes total.
We verify your background and add you to the machine learning pool.
When a project needs machine learning expertise, we invite matching people from the pool to that specific listing. It names the rate, the hours, and the client, and any hiring decision is made there.
What to expect
This listing does not accept or reject candidates, so you will not get a decision on it. We reach out when a project matches your background. Depending on what our clients are running, that can be within a week or several months.
Finishing the domain expert interview and joining every network you qualify for both improve your odds of being matched. You only need to sign up once to be eligible across all of them.
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.
Responsibilities
- Writing a modeling problem from a system you actually shipped, with the data, the objective, and the constraint, plus the reference answer a model's attempt gets graded against.
- Grading model-written training and evaluation code: whether the loss matches the objective, whether the eval set leaks, whether the ablation supports the conclusion drawn from it.
- Flagging where a model proposes an approach that would train cleanly and still fail in production, given distribution shift, label noise, or a metric that rewards the wrong behaviour.
Required skills
- Professional experience training, evaluating, or deploying machine learning systems.
- Clear written communication, since most of the work involves explaining your reasoning.
- Comfort with ambiguous tasks, and willingness to flag unclear instructions.
Eligibility
Work arrangement: Fully remote
- Please note: We are unable to support H1-B or STEM OPT candidates at this time.
Compensation details
- Comparable machine learning projects have posted at $70 to $120 an hour, set per project by scope and depth.
- Payments are weekly on Stripe or Wise based on services rendered.
More about the hiring companyMercor
