Job Description
Sound earth-science reasoning depends on correct application of geological, atmospheric, and environmental principles — the same discipline AI systems need to learn before they can be trusted with scientific analysis. Chegg is seeking earth science professionals to evaluate AI-generated content, build authoritative reference answers, and flag flawed scientific reasoning. Fully remote and asynchronous.
Core Responsibilities
- Evaluate AI-generated responses to geology, meteorology, oceanography, and environmental science questions for accuracy, reasoning quality, and completeness
- Write reference-standard solutions with correct scientific reasoning and terminology with correct established earth-science principles and data interpretation methods and clear explanations that AI models learn from
- Identify factual errors, misapplied scientific principles, or flawed data interpretation in AI-produced content, tagging the specific error category
- Compare and rank multiple AI responses to the same problem, explaining which best reflects scientific accuracy and clarity
- Test whether AI systems handle ambiguous or data-heavy scientific scenarios correctly
- Create realistic synthetic case studies covering geological, climate, and environmental phenomena used to train and evaluate models
- Contribute to rubric design — defining scoring criteria such as accuracy, scientific rigor, and clarity — used to benchmark AI performance at scale
- Complete asynchronous task batches independently — no scheduled calls or fixed hours required
Key Qualifications
- Master’s degree or PhD in Geology, Earth Science, Environmental Science, or a related field (or equivalent recognized qualification); relevant experience is a plus — postgraduate and doctoral graduates welcome
- Strong grounding in geological, atmospheric, or environmental science principles and data interpretation
- Ability to evaluate scientific claims for accuracy and internal consistency
- Sharp eye for subtle factual, logical, or methodological error — can detect and explain flawed reasoning in plain English
- Self-directed, detail-oriented, and comfortable delivering quality work asynchronously
Nice to Have
- Research or field experience in geology, climatology, or environmental science
- Proficiency with remote sensing and satellite imagery analysis (ENVI, Google Earth Engine) or climate modeling software
- Familiarity with GIS tools (ArcGIS, QGIS) or geochemical analysis techniques
- Prior experience in content review, QA, or AI/ML data annotation projects
Why Chegg
- Fully remote and flexible — no fixed schedule
- Task-based commitment, typically 10–40 hours per week
- Real-world challenges with direct impact on AI accuracy and safety
- Pathway to ongoing projects for high-quality contributors