AI Trainer; Life Sciences), Computational Scientist

Create and assess challenging AI tasks in computational life science, reviewing code, analyses, models, and experiments.

This remote contractor role requires at least 15 hours per week and pays $60 to $120 per hour equivalent, paid per task that meets project specifications.

Compensation

Contract, part-time

Engagement:
Remote

Location:

Open in 52 countries

• United States
• Algeria
• Argentina
• Austria
• Bahrain
• Bangladesh
• Belgium
• Brazil
• Canada
• Chile
• Colombia
• Denmark
• Egypt
• France
• Germany
• Ghana
• Greece
• India
• Indonesia
• Italy
• Japan
• Jordan
• Kazakhstan
• Kenya
• Kuwait
• Kyrgyzstan
• Lebanon
• Malaysia
• Mexico
• Morocco
• Netherlands
• Nigeria
• Oman
• Pakistan
• Palestine
• Peru
• Philippines
• Portugal
• Qatar
• Saudi Arabia
• Singapore
• South Africa
• Spain
• Sri Lanka
• Switzerland
• Taiwan
• Thailand
• Tunisia
• United Arab Emirates
• United Kingdom
• United States
• Uzbekistan
• Vietnam

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.

• Pay: $60 to $120 per hour equivalent, paid per task that meets project specifications and quality requirements.
• Schedule:
  
  At least 15 hours per week and less than 20 hours per week.
• Location:
  
  Open to candidates in the United Arab Emirates, Argentina, Austria, Bangladesh, Belgium, Bahrain, Brazil, Canada, Switzerland, Chile, Colombia, Germany, Denmark, Algeria, Egypt, Spain, France, the United Kingdom, Ghana, Greece, Indonesia, India, Italy, Jordan, Japan, Kenya, Kyrgyzstan, Kuwait, Kazakhstan, Lebanon, Sri Lanka, Morocco, Mexico, Malaysia, Nigeria, the Netherlands, Oman, Peru, the Philippines, Pakistan, Palestine, Portugal, Qatar, Saudi Arabia, Singapore, Thailand, Tunisia, Taiwan, the United States, Uzbekistan, Vietnam, and South Africa.
• 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.

Experience building AI‑training tasks, reference answers, rubrics, graders, or benchmark problems is useful.

Experience reviewing technical submissions or conducting long‑horizon or agentic AI evaluations is also relevant.

• Scientific tools such as Num Py, Sci Py, pandas, Biopython, PyTorch, JAX, or comparable software.
• Public computational publications, research code, bioinformatics pipelines, open‑source scientific software, datasets, models, notebooks, or technical projects.
• Experience applying programming judgment to scientific analyses and checking whether results can be reproduced.

AI training is the human work behind systems that learn from examples, including reviewing code, scientific analyses, and model outputs.

People with strong technical or scientific experience help set reliable standards for…