AI Trainer (Life Sciences), Computational Life Scientist

You will create difficult, realistic tasks that test advanced AI systems on computational life-science problems. You will also assess whether model-generated technical work is correct, scientifically sound, reproducible, and free of serious errors.

• Create computational life-science tasks, clear instructions, reproducible environments, reference solutions, and objective evaluation criteria.
• Review model-generated code, analyses, models, experiments, and other technical deliverables.
• Find invalid biological assumptions, methodological errors, data leakage, statistical problems, and reproducibility failures.
• Set standards for deciding whether technical solutions are correct and scientifically sound.

This is a remote, part-time contractor role for an intermediate-level contributor. The work requires prior experience training, evaluating, benchmarking, or improving AI systems on scientific or technical tasks.

• Schedule: At least 15 hours per week and less than 20 hours per week.
• Language: Fluent in English.
• Core skills: Strong practical Python proficiency and deep expertise in at least one relevant area, such as biology, computational biology, bioinformatics, medicine and health, biomedical science, neuroscience, genomics, ecology, or evolution.
• Experience: Hands-on work with computational modeling, simulation, bioinformatics, biomedical analysis, statistics, or reproducible research.
• AI training background: Paid experience training, evaluating, benchmarking, or improving AI systems on scientific or technical tasks.