Geology Quality Assurance Lead

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We help people start and grow durable freelance careers teaching AI by consolidating opportunities, providing training workflows, and supporting professional development in this fast-growing industry.

Why AI training matters

AI systems learn from examples prepared and reviewed by people. Work in AI training—also called data labeling, annotation, or human feedback—keeps models accurate, safe, and useful. Contributors do remote, flexible, impactful work such as evaluating model outputs, creating calibration materials, and shaping how AI explains scientific topics.

The role

OpenTrain is hiring a Geology Quality Assurance Lead to oversee scientific quality for geology and earth-science text outputs and trainer submissions. This is a remote contractor, part-time role for US-based contributors, expected at 20+ hours per week and paying $70/hour.

You will focus on quality monitoring, scientific review, trainer and QA communication, documentation, onboarding support, and continuous process improvement for remote geology AI training projects.

What you'll do

• Review geology explanations, earth-science summaries, map and data interpretations, geologic-process descriptions, climate and hazard explanations, and step-by-step reasoning for scientific accuracy.
• Provide precise written feedback to trainers and QAs, flag misleading or geologically impossible claims, and escalate recurring or critical quality issues.
• Maintain and update style guides, trackers, FAQs, example sets, calibration tasks, and onboarding materials to reflect current standards.
• Communicate project changes, workflow updates, and review standards to distributed trainer and QA teams.
• Support onboarding and training calls, run calibration exercises, and follow up on activation and remediation tasks.
• Identify patterns of error, recommend process improvements, and help implement rubric adjustments to improve overall dataset quality.

Requirements

• Degree in Geology, Earth Sciences, Geoscience, Environmental Science, Geophysics, Geochemistry, Hydrology, Paleontology, Oceanography, or a closely related field.
• 3+ years of geology or earth science experience in research, teaching, fieldwork, consulting, geospatial analysis, academic review, or science communication.
• Strong grasp of plate tectonics, rock cycle, mineralogy, stratigraphy, geologic time, structural geology, geomorphology, natural hazards, climate systems, hydrology, and earth system processes.
• Excellent written English for clear, precise feedback and team coordination.
• Ability to evaluate content against detailed rubrics and identify flawed geologic reasoning or unsupported claims.
• Preferred: familiarity with GIS, remote sensing, geologic mapping, core/log interpretation, geochemical or climate datasets, Python or R, or scientific visualization.
• Preferred: experience supporting remote teams and familiarity with AI training, data annotation, LLM evaluation, or rubric-based review.

Tools, logistics, and scope

This role centers on text evaluation (RLHF and evaluation-rating tasks) and requires regular communication with distributed trainer and QA teams. You will use collaborative tools such as Google Docs, Google Sheets, Discord, trackers, and dashboards to manage feedback and documentation.

OpenTrain hires and contracts directly for this role. The position is a contractor, part-time engagement paid at $70/hour, available to contributors based in the United States who can work 20+ hours per week.

Who should apply and next steps

Apply if you have expert earth-science knowledge, clear written English, and experience judging scientific accuracy against rubrics. This role suits experienced geoscientists who enjoy mentoring remote teams and improving annotation quality for AI systems.

To apply, create an OpenTrain account, complete your profile with your geology qualifications and experience, and submit your interest for the Geology Quality Assurance Lead role. Successful applicants will participate in calibration tasks and onboarding to demonstrate review standards.