M
AI Trainer (Life Sciences)
micro1
Contract type
Freelance
Work mode
Remote · Worldwide
Experience
3 years
Job description
micro1 is looking for Computational Life Scientists with prior professional AI-training or model-evaluation experience to support a project focused on improving advanced AI systems. The role involves creating challenging technical tasks, evaluating model-generated code and analyses, and establishing objective standards for correct solutions.
At a glance
- Employment
- Contract · Independent contractor
- Work mode
- Remote · Worldwide
- Pay
- USD 60 – 120 / hour
What you'll do
- Create realistic computational life-science tasks that challenge advanced AI models.
- Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
- Evaluate model-generated code, analyses, models, experiments, and technical deliverables.
- Identify invalid biological assumptions, methodological errors, data leakage, statistical issues, or reproducibility failures.
What we're looking for
- Prior paid experience training, evaluating, benchmarking, or improving AI systems on scientific or technical tasks.
- Strong practical proficiency with Python.
- Deep expertise in at least one relevant life-science specialization.
- Hands-on experience using computational methods for modeling, simulation, bioinformatics, biomedical analysis, statistics, or reproducible research.
- Relevant specializations may include biology, computational biology, bioinformatics, medicine and health, biomedical science, neuroscience, genomics, ecology, and evolution.
- Public proof of skill such as peer-reviewed publications or preprints involving computational methods, public research code or bioinformatics pipelines, Google Scholar, ORCID, or equivalent research profiles, PhysioNet or other biomedical competition results, open-source scientific software contributions, or public datasets, models, notebooks, or technical projects.
Nice to have
- Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
- Experience reviewing other AI trainers' technical submissions.
- Experience with NumPy, SciPy, pandas, Biopython, PyTorch, JAX, or comparable scientific tools.
- Prior experience with long-horizon or agentic AI evaluations.
- Availability to begin immediately.
How to get hired
- 1Submit your application, AI-training experience, specialization, and public technical evidence.
- 2Complete an AI interview containing technical and integrity checks.
- 3Complete a hiring-manager review.
- 4If selected, complete project onboarding and begin your first assigned task.