Job Description
Sound biological reasoning depends on correct application of scientific principles across molecular, cellular, and organismal levels — the same discipline AI systems need to learn before they can be trusted with life-science content. Chegg is seeking biology 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 biology questions spanning genetics, cell biology, ecology, and evolution for accuracy, reasoning quality, and completeness
- Write reference-standard solutions with correct biological reasoning and terminology with correct established biological principles and experimental methodology and clear explanations that AI models learn from
- Identify factual errors, misapplied biological concepts, or flawed experimental reasoning 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 multi-concept biology questions correctly
- Create realistic synthetic case studies spanning genetics, ecology, and molecular biology 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 Biology or a related life-science field (or equivalent recognized qualification); relevant experience is a plus — postgraduate and doctoral graduates welcome
- Strong grounding in genetics, cell biology, ecology, or evolutionary biology
- Research or teaching experience involving biological concepts and experimental design
- 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
- Published research or graduate teaching experience in a biological subfield
- Proficiency with bioinformatics tools (BLAST, R/Bioconductor) or phylogenetics software
- Hands-on lab experience with PCR, CRISPR, or other molecular biology 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