As a Geology Quality Assurance Lead, you will review AI-generated geology content, trainer submissions, and quality assurance work. You will check scientific accuracy, geologic reasoning, terminology, spatial and temporal context, units, data interpretation, clarity, formatting, instruction following, and rubric alignment.
- Review geology explanations, earth science summaries, geologic processes, map and data interpretations, climate and hazard explanations, and step-by-step reasoning.
- Identify misleading, overconfident, geologically impossible, poorly contextualized, or unsupported claims.
- Write clear feedback, escalate recurring or critical quality issues, and answer questions from trainers and quality reviewers.
- Share project changes, workflow updates, and review standards with trainers and quality assurance teams.
- Maintain style guides, trackers, FAQs, examples, calibration tasks, and onboarding materials.
- Support onboarding and training calls for remote expert teams and help improve review processes.
What it pays and takes
This is an expert-level, part-time contractor role for candidates based in the United States. The work requires strong geology or earth science knowledge and clear written English for detailed feedback and team coordination.
- Pay: $70 per hour.
- Time: 20+ hours per week.
- Location: United States.
- Language: English.
- Education: A degree in geology, earth sciences, geoscience, environmental science, geophysics, geochemistry, hydrology, paleontology, oceanography, or a closely related field.
- Experience: At least 3 years in geology or earth science research, teaching, fieldwork, consulting, geospatial analysis, academic review, science communication, or related work.
- Knowledge: Plate tectonics, the rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
- Core ability: Evaluate content against detailed rubrics and identify flawed geologic reasoning or unsupported claims.
- Helpful experience: GIS, remote sensing, geologic mapping, field methods, core or log interpretation, geochemical data, climate datasets, Python, R, or scientific visualization.
- A strong plus: Remote team support, AI training, data annotation, large language model evaluation, scientific quality assurance, academic review, or rubric-based review.
- Helpful tools: Discord, Google Sheets, Google Docs, trackers, dashboards, and project management tools.
- Documentation experience maintaining materials and calibration resources for distributed teams is helpful.
How it works
Apply on OpenTrain with your resume, then complete the application on the hiring site.
About AI training work
AI training work is the human side of building artificial intelligence: people review examples and model responses so AI systems learn to provide more accurate and useful results. Experienced specialists are needed for tasks that require careful judgment in fields such as geology and earth science.