Machine Learning Expert

Mercor; India; Remote; INR 9,055,000 - 15,522,000; Part time

Benefits offered by this job

Remote work

Weekly payments (Stripe/Wise)

Job summary

Mercor is seeking a Machine Learning Expert for fully remote, independent contractor work. You will engage on projects that involve training, evaluating, and deploying ML systems, with emphasis on explaining reasoning and handling ambiguous instructions.

Compensation is project-based with weekly payments via Stripe or Wise; typical rate ranges from $70 to $120 per hour depending on scope and depth. The posting notes no decision on candidates and matchmaking based on client needs.

Qualifications

• 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.

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.

Job description

Machine Learning ExpertCompany: MercorCompensation: $70Commitment: Talent networkLocation: RemoteReferral Link: https://t.mercor.com/szac9

What the work looks like

• 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

Comparable projects

Comparable machine learning projects have posted at $70 to $120 an hour, set per project by scope and depth.

What we're looking for

• 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

Where you trained matters less than whether you have put models in front of real users and dealt with what came back.

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.

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.