Geology Quality Assurance Lead (Remote, Contract)

About OpenTrain

OpenTrain is the #1 platform for people building careers in AI training and data labeling. We help freelancers find and grow work teaching AI: consolidate opportunities, build a unified portfolio, and apply in minutes — all from one place.

We hire and contract subject-matter experts and reviewers to evaluate model outputs, develop guidelines, and improve annotation quality. This role is an OpenTrain engagement supporting geology and earth-science projects used to teach and evaluate AI systems.

About AI training and why it matters

AI training (data labeling, annotation, and human feedback) is how modern models learn correct behavior and scientific reasoning. Contributors annotate, rate, and evaluate model outputs so systems become more accurate, reliable, and useful.

As a QA Lead you help ensure geological accuracy, clear reasoning, and consistent reviewer judgment — work that directly shapes how state-of-the-art AI handles earth-science topics.

The role

You will lead quality assurance for geology and earth-science AI training projects. This is a remote contractor role focused on reviewing AI-generated content and reviewer work, enforcing rubrics, writing precise feedback, and improving QA workflows and documentation.

• Oversee reviewer outputs and AI-generated geology content for scientific accuracy, geologic reasoning, and guideline adherence.
• Write clear, structured feedback to trainers and QAs and help calibrate remote contributors.
• Maintain and improve style guides, FAQs, honeypots, calibration tasks, trackers, and onboarding materials.
• Support onboarding sessions and training calls for remote contributors.
• Identify recurring quality problems and suggest process improvements to raise consistency and accuracy.

What you'll do day-to-day

• Evaluate AI outputs and reviewer judgments against project rubrics and examples.
• Check geologic explanations, process descriptions, map and data interpretations, climate or hazard explanations, and step-by-step reasoning.
• Document errors, create exemplar corrections, and maintain trackers and calibration tests.
• Communicate updates, clarifications, and rule changes to remote contributors.
• Participate in onboarding and calibration sessions and help scale reviewer capabilities.

Requirements

• Strong expertise in geology or a closely related earth science discipline (plate tectonics, mineralogy, stratigraphy, geologic time).
• Proven ability to judge scientific accuracy, geologic reasoning, and contextual quality in technical content.
• Excellent written English and experience giving structured, technical feedback.
• Comfort with documentation and remote collaboration tools (Sheets, Docs, Discord, etc.).
• Experience in geology research, teaching, fieldwork, environmental consulting, geospatial analysis, academic review, or science communication.
• Familiarity with AI training, rubric-based review, LLM evaluation, or scientific QA is a strong plus.
• Location: United States only; English required.
• Availability: 20+ hours per week; contractor, part-time.

Helpful background and technical skills

• Advanced degree in geology, geoscience, environmental science, geophysics, geochemistry, hydrology, oceanography, paleontology, or a closely related field.
• Familiarity with GIS, remote sensing, geologic mapping, core/log interpretation, geochemical or climate datasets, or scientific visualization.
• Experience with Python or R for simple data checks or plotting is helpful but not required.
• Previous experience leading or supporting remote teams of researchers, reviewers, or annotators is beneficial.

Rate, format, and project details

This is a remote contractor, part-time role for US-based contributors. Pay is up to $70/hour and the position typically requires 20+ hours per week.

Work centers on evaluation and RLHF-style rating tasks (evaluation_rating and RLHF label types). You will use documentation, calibration tasks, and reviewer feedback to keep outputs aligned with scientific standards.

Who should apply and how to get started

This role is a strong fit for experienced geologists, earth scientists, and technical reviewers who enjoy improving model outputs and coaching remote contributors. If you care about scientific accuracy, structured feedback, and clear documentation, apply.

To apply, create or use your OpenTrain profile, confirm your US location and availability, and submit your experience highlighting geology expertise and any prior QA or annotation work. OpenTrain will manage contracting and help you build a stronger AI training portfolio.