Biology AI Training Expert (PhD, Remote, $80–90/hr)
Bring your PhD in biology to improve AI systems: review and refine biology prompts, scenarios, and model outputs on a part-time, remote contract at $80–90/hr. Work <20 hrs/week on text-based evaluation and generation tasks with OpenTrain AI.
Generative AI & RLHF
100% Remote Hourly · $80–$90/hr
$80–$90/hr
Compensation
Worldwide
Eligibility
Entry
Experience
Jul 15, 2026
Posted
Open worldwide
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OpenTrain is the leading platform for people building careers in AI training and data labeling. We connect domain experts with paid work that directly shapes how modern AI systems behave, and creating an OpenTrain account is free.
Why AI training matters for biology
AI models learn from human-created and reviewed examples. In biology, expert reviewers ensure scientific accuracy, depth, and responsible framing so models can reason about complex concepts correctly. This is a fast-growing, remote-friendly way to use scientific expertise outside traditional lab roles.
The role
OpenTrain AI is hiring a Biology AI Training Expert to review, create, and refine biology-related prompts, scenarios, questions, and explanations used in AI development. You will provide expert feedback that improves accuracy, relevance, and scientific rigor in model outputs and training data.
This is a contract, part-time role (<20 hours/week), worldwide and remote. Work is text-focused and centers on evaluation and text-generation tasks.
Work type: Contract, Part-time, remote, worldwide
Time commitment: Less than 20 hours per week
Data type: Text (evaluation and generation)
Labeling tasks: Evaluation rating and text generation
What you'll do
You will apply your biological expertise to assess and improve training data, craft rigorous scientific scenarios, and document rationale so teams can reproduce decisions and iterate quickly.
Critically evaluate biology-related data, prompts, and content for scientific accuracy and clarity.
Create, review, and refine scientific scenarios, questions, and explanations for complex biological problems.
Provide expert-level feedback to improve the accuracy, relevance, and depth of AI training datasets and model outputs.
Document findings, methodologies, and rationale to support transparency and reproducibility.
Participate in iterative review cycles and knowledge-sharing sessions with interdisciplinary teams.
Requirements
The role requires demonstrated scientific training and the ability to communicate clear, reproducible feedback. Preserve the stated requirements when applying.
PhD in biology or a closely related life science field (required).
Strong understanding of core biological principles and scientific reasoning.
Experience reviewing research or analyzing scientific data with attention to rigor.
Ability to critique biology-related prompts, scenarios, and explanations for scientific accuracy.
Clear written communication and ability to provide documented rationale.
Comfort working independently on iterative review tasks.
Fluent English (work language).
Helpful background & who should apply
Candidates who have worked on interdisciplinary projects, contributed to science-technology collaborations, or who have prior exposure to AI/ML workflows will be especially successful, though AI-specific experience is not required.
The posting is listed as entry level: it is suitable for early-career PhD holders as well as more experienced researchers who want part-time, remote work influencing AI systems.
Prior contributions to interdisciplinary scientific or technology-focused projects (helpful).
Exposure to AI workflows or model evaluation (a plus).
Compensation, schedule, and how to apply
Compensation is hourly at USD 80–90 per hour. This is a contractor role with flexible hours; expected workload is under 20 hours per week. OpenTrain AI is the hiring organization and will contract selected experts.
To apply, sign in or create a free OpenTrain account to submit your profile and indicate your availability and relevant expertise.
Pay: USD 80–90 per hour (pay-per-hour)
Hours: Less than 20 hours/week; flexible scheduling
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