M
AI Trainer (Physical Sciences)
micro1
Contract type
Freelance
Work mode
Remote · Worldwide
Experience
3 years
Job description
micro1 is looking for Computational Physical 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 physical-science tasks that challenge advanced AI models.
- Develop task instructions, reproducible environments, reference solutions, and evaluation criteria.
- Evaluate model-generated calculations, code, simulations, models, and technical deliverables.
- Identify invalid assumptions, numerical errors, physically impossible results, incorrect methods, 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 physical-science specialization.
- Hands-on experience using computational methods for modeling, simulation, numerical analysis, data analysis, or reproducible research.
- Relevant specializations may include physics, astronomy and cosmology, materials science, chemistry, computational physics, computational chemistry, and scientific simulation.
- Public proof of skill such as peer-reviewed publications or preprints involving computational methods, public simulation or analysis code, Google Scholar, ORCID, arXiv, or equivalent research profiles, open-source scientific software contributions, reproducible notebooks, models, datasets, or simulations, public benchmarks, experiments, or technical projects.
Nice to have
- Experience creating AI-training tasks, reference answers, rubrics, graders, or benchmark problems.
- Experience with NumPy, SciPy, SymPy, Astropy, PyTorch, JAX, or comparable scientific tools.
- Experience validating simulations or models against analytical results, observations, or experimental data.
- 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.