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Biology Quality Assurance Lead (QAL)

SME Careers The United States

Education

Any

Type

Pay Rate

$75/task

Listed

3d ago

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BIOLOGYQAL-25-503

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About this Role

In this hourly, remote contractor role, you will work as a Biology Quality Assurance Lead (QAL) to 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 that all contributors follow the expected quality standards.

You will assess work for scientific accuracy, biological reasoning, terminology correctness, experimental logic, unit consistency, safety awareness, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong biology expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your biology quality leadership will directly help improve the world’s premier AI models by ensuring that biology training data is accurate, logically sound, clearly explained, safety-aware, well-documented, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

Important:
There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

### Key Responsibilities
- Quality monitoring: Spot-check biology items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
- Scientific review: Evaluate AI-generated biology explanations, biological mechanisms, experimental reasoning, genetics problems, diagrams/descriptions, terminology, and problem-solving steps for correctness and clarity.
- Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and biology-specific review standards.
- Question handling: Respond to trainer/QA questions clearly and promptly, especially around biological reasoning, terminology, experimental design, methods, safety concerns, scientific claims, 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 biology 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 biology-specific review requirements.
- Quality alignment: Ensure all trainers and QAs apply biology guidelines consistently and understand updates as projects evolve.
- Risk and safety review: 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.
- Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for biology AI training projects.

### Your Profile
- 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.

Requirements

  • Advanced degree or strong hands-on professional experience in the domain
  • Ability to pass domain-specific qualification assessments
  • Eligible to create a verified account on Deel (for payments/compliance)
  • Proficiency in English (for instructions and feedback)
  • Must be located in one of the 40+ supported countries (e.g., The United States)

Compensation Analysis

Don't just label data—build a career. SME Careers is unique in the AI training space because it offers a transparent growth ladder. High performers aren't just kept in the queue; they are promoted to Quality Analysts and Project Managers. With weekly transparent payments via Deel and the freedom to work on your own schedule, this is built for modern experts who want long-term engagement.

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Frequently Asked Questions

Is there room for advancement?

Yes. This is a key feature of the platform. They explicitly list a career path: Data Trainer -> Quality Analyst -> QA Lead -> Project Manager. Consistent high-quality work can lead to leadership roles.

How do payments work?

Payments are processed weekly through Deel. This ensures tax compliance and allows them to hire freelancers from over 40 countries securely.

Is the work ongoing or project-based?

Work is project-based, which means assignments can vary in duration and availability. However, top performers often get priority access to new projects.

Is this just labeling data?

No. This is closer to academic research. You will likely be writing or verifying complex proofs, solving advanced equations, or checking the logic of a model's step-by-step reasoning. The goal is to teach AI systems to reason deeply in your field.

Do I need a PhD?

For the highest pay tiers in this category, a PhD (or current enrollment) is usually expected. However, the most important factor is your ability to pass the domain assessment. If you can solve the problems, the degree is secondary.

Is the work continuous?

Work in niche fields is often project-based. A specific "campaign" (e.g., training a model on Quantum Mechanics) might last for a few weeks. It is best to treat this as a high-paying fellowship or grant rather than a permanent daily job.

Who is behind SME Careers?

SME Careers is the expert talent division of SuperAnnotate, a leading AI data infrastructure platform. They connect domain experts with high-level AI training projects.