STEM Technical Reviewer for AI Training

Role Overview

Apply deep expertise in a STEM discipline to help evaluate and improve AI systems through rigorous technical problem-solving, scientific reasoning, data analysis, and Python-based validation. You will solve, review, and validate challenging domain-specific work, including assessing whether AI-generated answers are technically correct. This is a coding-heavy role, and candidates must use Python coding agents in their workflow.

Key Responsibilities

• Solve complex scientific, mathematical, and technical problems within your area of expertise.
• Review AI-generated solutions for factual, mathematical, and scientific accuracy.
• Identify flawed assumptions, reasoning errors, omitted constraints, and subtle technical issues.
• Create clear, reproducible reference solutions and explain corrections and technical reasoning.
• Use Python for scientific computing, data analysis, simulations, and solution validation.
• Interpret equations, experimental findings, datasets, technical diagrams, and scientific literature when relevant.
• Perform sanity checks on numerical and analytical results, compare alternative approaches, and determine whether conclusions are supported by evidence.

Qualifications

• Deep expertise in at least one STEM or scientific field, including chemistry, biology, mathematics, physics, earth science, geoscience, environmental science, robotics, or a directly relevant adjacent quantitative discipline.
• Practical Python proficiency and experience using coding agents with Python in your workflow.
• Strong scientific, mathematical, or quantitative problem-solving skills.
• Ability to assess assumptions, constraints, edge cases, and 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. No specific library is required.
• Expertise may come from academic research, industry, teaching, engineering, independent technical work, or other demonstrated experience. A specific degree or minimum years of experience are not required if you can demonstrate strong subject-matter expertise.

Work Terms

• Global, fully remote independent contractor engagement.
• Approximately 15 hours per week.
• Flexible schedule, with control over the days and hours worked, including weekends if desired.

Compensation

• Advertised rate of $80 to $150 per hour.
• Compensation is output-based and paid per task that meets project specifications.
• Task completion time varies based on the expert''s experience and workflow.

Application Process

• Submit an application and complete screening questions.
• Complete an AI interview of approximately 30 minutes.
• Proceed through a hiring manager review.