Biology QA Lead - Remote

About the role

This is an hourly, remote contractor position where you will oversee quality, consistency, and trainer performance across biology AI training projects. You will review AI-generated biology content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure all contributors follow expected quality standards.

Responsibilities

• Spot-check biology items, identify quality issues, provide ongoing feedback through direct messages (DMs), and escalate recurring or critical issues.
• Evaluate AI-generated biology explanations, biological mechanisms, experimental reasoning, genetics problems, diagrams/descriptions, terminology, and problem-solving steps for correctness and clarity.
• Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and biology-specific review standards.
• Respond to trainer/QA questions clearly and promptly, especially around biological reasoning, terminology, experimental design, methods, safety concerns, scientific claims, and rubric interpretation.
• DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
• Create and maintain biology project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
• Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and biology-specific review requirements.
• Ensure all trainers and QAs apply biology guidelines consistently and understand updates as projects evolve.
• Flag unsafe, misleading, or overconfident biology recommendations, especially where lab procedures, biological samples, pathogens, genetic engineering, health claims, environmental impact, or biosafety may be affected.
• Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for biology AI training projects.

Requirements

• Bachelor’s, Master’s, or PhD degree in Biology, Molecular Biology, Cell Biology, Genetics, Microbiology, Biochemistry, Ecology, Evolutionary Biology, Neuroscience, Physiology, or a closely related field.
• Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear scientific feedback in English.
• 3+ years of professional experience in biology research, laboratory work, teaching, scientific writing, technical review, quality control, biotechnology, life sciences, or related workflows.
• Strong understanding of core biology topics such as cell biology, molecular biology, genetics, evolution, ecology, physiology, microbiology, biochemistry, immunology, anatomy, developmental biology, and experimental design.
• Ability to evaluate biology content against detailed rubrics and identify issues such as incorrect assumptions, flawed experimental reasoning, inaccurate terminology, missing context, unsafe recommendations, hallucinated facts, incomplete explanations, or misleading scientific claims.
• Familiarity with common biology tools or workflows such as laboratory documentation, microscopy, PCR/qPCR, sequencing, gel electrophoresis, cell culture, ELISA, bioinformatics basics, statistical interpretation, safety data sheets, or scientific literature review is preferred.
• Experience leading or supporting remote teams of trainers, annotators, reviewers, researchers, technical writers, educators, or QAs is strongly preferred.
• Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
• Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
• Experience with AI training, data annotation, large language models, prompt/response evaluation, scientific content QA, or rubric-based LLM evaluation is a strong plus.