Biology Reasoning Evaluator (PhD)

About OpenTrain AI

OpenTrain is the #1 platform for building careers in AI training and data labeling. We hire and contract contributors directly to work on cutting-edge AI tasks that shape how models behave.

Working with OpenTrain means joining a fast-growing industry where remote, flexible, and impactful work is routine—ideal for researchers and specialists who want to apply their domain expertise to improve AI systems.

• OpenTrain hires and contracts contributors for AI training, evaluation, and annotation projects.
• Work remotely, choose flexible hours, and contribute to how real AI products learn from expert human feedback.

About AI Training Work

AI training (data labeling and model evaluation) is the human side of building intelligent systems: experts review model outputs, correct errors, and provide high-quality examples that models learn from.

This role focuses on model evaluation and RLHF-style review for biological reasoning and methodology—work that directly improves model reliability on scientific tasks.

• Tasks include reading model responses, applying detailed rubrics, and writing clear exemplar solutions.
• Projects are remote and typically offer flexible schedules with defined minimum availability during active sprints.

The Role

We are hiring a Biology Reasoning Evaluator to review AI-generated biology responses for scientific correctness, methodological rigor, and clarity.

This is a contractor, part-time role paid per hour at USD 80/hour. Minimum availability is 17–20 hours per week; work is generally under 20 hours/week with preferred ~8-hour workdays during active sprints.

• Position type: Contractor, Part-time.
• Pay: USD 80 per hour (PAY_PER_HOUR).
• Location: Remote, worldwide.

What You’ll Do

You will read and evaluate AI-generated answers to complex biology prompts, apply evaluation rubrics, and produce clear feedback and exemplar explanations that models can learn from.

• Assess biological correctness, reasoning depth, and clarity of model responses.
• Identify and explain conceptual and methodological flaws in study design, methods, statistics, calculations, and interpretation.
• Fact-check claims against reputable public sources and provide precise references when required.
• Draft exemplar explanations or model solutions that show correct reasoning step-by-step.
• Rate and compare multiple responses using detailed rubrics and consistent standards.

Requirements

All requirements below are mandatory unless noted as a bonus. Candidates must be able to apply rigorous, reproducible scientific judgment in English at C1+ level.

• PhD in Biology or a closely related life science (Top-100 university preferred).
• Peer-reviewed publication record as first or co-author.
• Proven experience developing or critically reviewing complex biological content (manuscripts, advanced curricula, protocols, grant sections, computational analyses).
• Breadth across core areas (e.g., molecular/cell biology, genetics/genomics, biochemistry, physiology).
• Strong experimental design and statistics literacy; able to spot flaws in methods and interpretation.
• Exceptional scientific writing: clear, rigorous, step-by-step reasoning and correct terminology.
• Meticulous attention to detail, reproducibility, and consistent application of evaluation rubrics.
• Availability for minimum 17–20 hours per week; preferred cadence ~8 hours/day during active sprints.
• Bonus (not required): prior data labeling, RLHF, or AI model evaluation experience.

Onboarding and Workflow

Onboarding includes two paid assessments: a 1–2 hour qualification exam and a paid 1–2 hour project exam to confirm fit and rubric understanding. Successful completion is required to begin paid work.

Work flows are sprint-based. You will receive tasks, rubrics, and example responses; deliverables include ratings, written justifications, and exemplar answers. Consistent, reproducible application of rubrics is essential.

• Paid qualification exam: 1–2 hours.
• Paid project exam: 1–2 hours.
• Tasks: evaluate text outputs, provide ratings and written feedback, draft exemplar solutions.

Who Should Apply

Apply if you are a PhD-level biologist who enjoys careful scientific critique, clear scientific writing, and helping AI systems improve their scientific reasoning.

This role suits researchers, postdocs, or early-career faculty who want part-time, high-impact remote work that leverages domain expertise and contributes directly to AI quality.

• Ideal for domain experts seeking flexible, remote part-time work.
• A good fit if you can commit to the minimum weekly hours and produce consistent, reproducible evaluations.