STEM Expert for AI Training

Role Overview

Apply deep STEM expertise to help train and evaluate AI systems through rigorous technical problem-solving, scientific reasoning, data analysis, and Python-based validation. You will solve, review, and validate challenging domain-specific problems, including assessing whether AI-generated answers are technically correct.

Key Responsibilities

• Solve complex scientific, mathematical, or technical problems within your area of expertise.
• Review AI-generated solutions for factual, mathematical, and scientific accuracy.
• Identify incorrect assumptions, reasoning errors, missing constraints, and subtle technical mistakes.
• Create clear, reproducible reference solutions and explain corrections.
• Use Python for scientific computation, data analysis, simulations, or solution validation.
• Interpret equations, experimental results, datasets, technical diagrams, and scientific literature when relevant.
• Perform sanity checks, validate numerical or analytical results, and compare alternative approaches against available evidence.

Qualifications

• Strong expertise in at least one relevant STEM or scientific field, including chemistry, biology, mathematics, physics, earth science, geoscience, environmental science, linguistics, computational linguistics, robotics, or a directly relevant adjacent scientific or quantitative discipline.
• Practical proficiency with Python and strong scientific, mathematical, or quantitative problem-solving skills.
• Ability to evaluate assumptions, constraints, edge cases, and potential sources of error carefully.
• Ability to communicate complex technical concepts and solutions clearly.
• Experience validating, reviewing, or troubleshooting technical work.
• Useful Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries, though no particular library is required.
• Expertise may come from research, industry, teaching, engineering, independent technical work, or other demonstrated experience. A specific degree or minimum number of years of experience is not required if strong expertise can be demonstrated.

Work Terms

• Global, fully remote independent contractor engagement.
• Approximately 15 hours per week.
• Flexible schedule, with freedom to choose working hours and days, including weekends.

Compensation

• Compensation is listed at $50 to $100 per hour.
• Payment is output-based and issued per task that meets project specifications. Task completion time may vary by experience and workflow, and minimum submission requirements apply.

Application Process

• Submit an application and complete screening questions.
• Complete an approximately 30-minute AI interview.
• Proceed to hiring manager review.