Life & Environmental Sciences Team Lead
smeDenver, CO
Life & Environmental Sciences Team Lead
L5
smeDenver, COyesterday
Occupations
Natural Sciences ManagersEnvironmental Scientists and Specialists, Including HealthLife Scientists, All OtherIndustries
Other Scientific and Technical Consulting ServicesEnvironmental Consulting ServicesResearch and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)Job TitleYour profile Bachelor's, Master's, PhD, or equivalent professional experience in Biology, Environmental Science, Ecology, Conservation Biology, Earth Science, Public Health, Agriculture, Marine Science, Sustainability, Life Sciences, or a related field. Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.3+ years of experience in life science research, environmental science, teaching, fieldwork, lab work, conservation, sustainability, science communication, academic review, or related scientific workflows. Strong understanding of biology, ecology, ecosystems, biodiversity, evolution, genetics, physiology, environmental systems, climate change, pollution, conservation, sustainability, and scientific methods. Ability to evaluate life/environmental science content against detailed rubrics and identify issues such as incorrect biological claims, oversimplified ecological relationships, unsupported environmental claims, flawed causal reasoning, unsafe recommendations, or misleading data interpretation. Familiarity with tools or methods such as field sampling, lab methods, ecological surveys, environmental impact assessment, GIS, statistics, climate/environmental datasets, literature review, or scientific visualization is preferred. Experience leading or supporting remote teams of researchers, educators, reviewers, environmental specialists, annotators, trainers, 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 documentation. Experience with AI training, data annotation, LLM evaluation, scientific QA, environmental content review, academic review, or rubric-based review is a strong plus.
Key responsibilities:
Quality monitoring: Spot-check life and environmental science items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
Scientific review: Evaluate AI-generated biology, ecology, environmental science, sustainability, conservation, climate, and life science explanations for accuracy, clarity, and scientific rigor.
Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and life/environmental-science-specific review standards.
Question handling: Respond to trainer/QA questions clearly and promptly, especially around biological concepts, ecosystems, environmental systems, data interpretation, sustainability claims, safety, and rubric interpretation.
Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
Documentation: Create and maintain life/environmental sciences project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and scientific review requirements.
Quality alignment: Ensure all trainers and QAs apply life and environmental science guidelines consistently and understand updates as projects evolve.
Risk review: Flag misleading environmental claims, unsupported health/ecology statements, unsafe experiment or field recommendations, flawed data interpretation, or overconfident scientific claims.
Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for life and environmental science AI training projects.
Skills & technologies
Biology Environmental Science Ecology Life Sciences AI Training LLM Evaluation Scientific Review Climate Systems Sustainability Trainer Feedback
Apply now
Level
SeniorL5
Location
Denver, CO
Occupation
Natural Sciences Managers
Industry
Other Scientific and Technical Consulting Services
Posted
yesterday
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