Geology Quality Assurance Lead

You will lead quality review for remote geology AI training projects. The work includes reviewing scientific content, supporting trainers and quality reviewers, answering project questions, following up on activation, maintaining documentation, supporting onboarding, and improving review processes.

• Review geology explanations, earth science summaries, geologic process descriptions, map and data interpretations, climate and hazard explanations, and step-by-step reasoning.
• Give precise written feedback and escalate recurring or critical quality issues.
• Flag misleading, overconfident, geologically impossible, or poorly contextualized claims.
• Update trainers and quality reviewers on project changes, workflow updates, and review standards.
• Maintain style guides, trackers, FAQs, examples, calibration tasks, and onboarding materials.
• Support onboarding and training calls for remote expert teams.
• Handle project questions, follow up on activation, and help improve review processes.

This is an expert-level, part-time contractor role for candidates in the United States. You should be comfortable reviewing detailed scientific content against clear standards and explaining quality issues in writing.

• $70 per hour.
• 20+ hours per week.
• Open to candidates in the United States.
• Strong English communication skills for written feedback and team coordination.
• A degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
• At least 3 years of experience in geology or earth science research, teaching, fieldwork, consulting, geospatial analysis, academic review, science communication, or related work.
• Strong knowledge of plate tectonics, the rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
• Ability to evaluate content against detailed rubrics and identify flawed geologic reasoning or unsupported claims.
• Preferred experience with GIS, remote sensing, geologic mapping, field methods, core or log interpretation, geochemical data, climate datasets, Python or R, or scientific visualization.
• Experience supporting remote teams or working with AI training, data annotation, AI model evaluation, scientific quality assurance, academic review, or rubric-based review is a strong plus.
• Helpful tools and background include Discord, Google Sheets, Google Docs, trackers, dashboards, project management tools, and documentation or calibration materials for distributed teams.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training is the human work behind systems that learn from examples, including reviewing explanations and rating model responses. Experienced specialists help identify errors and improve the quality of those examples.

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