We are sharing a specialised part-time consulting opportunity for experienced STEM and scientific-domain professionals with deep expertise in at least one technical field and strong scientific reasoning, quantitative problem-solving, data analysis, and Python skills to contribute to an advanced AI training and technical evaluation project.
Selected professionals will solve, review, and validate challenging scientific or mathematical problems within their area of expertise, develop reproducible reference solutions, and assess AI-generated answers for technical correctness. Candidates are not expected to be experts across every STEM discipline; deep expertise in one relevant domain is sufficient.
Key Responsibilities
Scientific & Technical Problem Solving
Solve complex scientific, mathematical, or technical problems within your primary area of expertise
Apply rigorous reasoning to assumptions, constraints, edge cases, and potential sources of error
Develop technically defensible solutions grounded in appropriate scientific principles
Interpret equations, experimental results, datasets, technical diagrams, or scientific literature where relevant
Perform sanity checks to ensure analytical and numerical results are physically or mathematically plausible
AI-Generated Solution Evaluation
Review AI-generated technical answers for factual, mathematical, and scientific correctness
Identify incorrect assumptions, reasoning errors, missing constraints, and subtle technical mistakes
Assess whether conclusions are adequately supported by calculations, evidence, or scientific reasoning
Compare alternative solution approaches and determine which methods are most appropriate
Explain corrections and technical weaknesses clearly and precisely
Python & Scientific Computation
Use Python for scientific computation, data analysis, simulations, or solution validation
Apply relevant tools such as NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries
Develop reproducible computational workflows supporting analytical conclusions
Validate calculations through numerical or symbolic methods where appropriate
Document computational reasoning sufficiently for independent review
Reference Solutions & Technical Communication
Develop clear, reproducible reference solutions for complex STEM problems
Document assumptions, methods, calculations, and final conclusions systematically
Explain technical concepts and corrections in clear written language
Distinguish well-supported conclusions from uncertain or unsupported claims
Maintain strong standards of accuracy, reproducibility, and technical clarity across deliverables
Ideal Profile
Deep expertise in at least one relevant STEM or scientific domain
Relevant disciplines may include Chemistry, Biology, Mathematics, Physics, Earth Science, Geoscience, Environmental Science, Robotics, or closely related quantitative fields
Practical proficiency with Python
Strong scientific, mathematical, or quantitative problem-solving skills
Ability to reason carefully about assumptions, constraints, edge cases, and sources of error
Experience validating, reviewing, or troubleshooting scientific or technical work
Ability to interpret quantitative data, technical material, and scientific evidence
Strong written communication skills and ability to explain complex technical concepts clearly
Expertise may come from academic research, industry, teaching, engineering, independent technical work, or other demonstrated professional experience
A specific degree or fixed number of years of experience is not required where strong domain expertise can otherwise be demonstrated
No prior experience in AI training or model evaluation is required
Engagement Details
Part-time independent contractor engagement
Fully remote and open to candidates worldwide
Compensation: $100–$150/hour
Expected commitment: approximately 15 hours per week
Schedule is flexible, including the option to work evenings or weekends
Compensation is output-based, with payment made for tasks that meet project specifications
Minimum submission requirements apply
Work will involve scientific problem solving, AI-output evaluation, Python-based analysis, validation, and reference-solution development
The selection process may include screening questions, an approximately 30-minute AI interview, and hiring-manager review
Selected professionals should be prepared to begin their first task within approximately 24–48 hours of completing onboarding
Roles are typically filled within approximately 48 hours
Work must be completed without using confidential or proprietary information belonging to any employer, client, institution, research group, or other third party
About the Platform
This opportunity is available through 24-MAG LLC. We connect experienced professionals with remote consulting opportunities across technical, evaluation, and project-based workstreams.
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