Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco our investors include BenchmarkGeneral CatalystPeter ThielAdam DAngeloLarry Summers and Jack Dorsey.
Position: Quality Control Lead Type:W2 Employment Compensation:$80$105/hour Location:Remote Commitment:40 hours/week
Role Responsibilities
Audit and evaluate detailed personas digital environments and tasks created by AI Training Scenario Designers. Ensure they are logically sound and properly structured.
Apply strict rubrics to score scenarios objectively. Ensure tasks challenge an AI agents ability to reason filter and prioritize.
Identify logical inconsistencies factual errors missing context and technical flaws such as invalid JSON structures.
Provide clear constructive and actionable feedback to scenario designers to refine their worlds and improve output.
Document outcomes by logging review results scores and feedback in Airtable and Crucible.
Technical / data comfortJSON familiarity Jira/Asana power user data analyst SQL/Python exposure.
Process & Systems thinking Operations managers technical PMs or systems designers.
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About the job Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco our investors include Benchmark General Catalyst Peter Thiel Adam DAngelo Larry Summers and Jack Dorsey. Position: Quality Control Lead Type: W2 Employment Compensation: $8...
About the job
Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco our investors include BenchmarkGeneral CatalystPeter ThielAdam DAngeloLarry Summers and Jack Dorsey.
Position: Quality Control Lead Type:W2 Employment Compensation:$80$105/hour Location:Remote Commitment:40 hours/week
Role Responsibilities
Audit and evaluate detailed personas digital environments and tasks created by AI Training Scenario Designers. Ensure they are logically sound and properly structured.
Apply strict rubrics to score scenarios objectively. Ensure tasks challenge an AI agents ability to reason filter and prioritize.
Identify logical inconsistencies factual errors missing context and technical flaws such as invalid JSON structures.
Provide clear constructive and actionable feedback to scenario designers to refine their worlds and improve output.
Document outcomes by logging review results scores and feedback in Airtable and Crucible.