STEM Technical Problem Solver for AI Training

Role Overview

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

Key Responsibilities

• Solve complex scientific, mathematical, and technical problems within your area of expertise.
• Develop rigorous solutions, including Python-based calculations or simulations when appropriate.
• Review AI-generated solutions for factual, mathematical, and scientific accuracy.
• Identify incorrect assumptions, reasoning errors, missing constraints, and subtle technical mistakes.

Qualifications

• Master''s or PhD-level expertise in at least one STEM or scientific discipline, particularly biology, chemistry, mathematics, physics, earth science, geoscience, environmental science, robotics, or a directly relevant adjacent scientific or quantitative field.
• Strong scientific, mathematical, or quantitative problem-solving skills.
• Practical proficiency with Python or another programming language.
• Experience using coding agents as part of your workflow.
• Relevant Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries, though no specific library is required.
• Expertise may be demonstrated through academic research, industry, teaching, engineering, independent technical work, or similar experience. A specific degree or minimum number of years of experience is not required when strong field expertise can be demonstrated.

Work Terms

• Independent contractor engagement, fully remote and open globally.
• Approximately 15 hours per week.
• Flexible schedule, with freedom to choose work hours and days, including weekends.
• Tasks are paid when they meet project specifications, and minimum submission requirements apply. Time required per task varies based on experience and workflow.
• Selected candidates should be ready to begin immediately and complete their first task within 24 to 48 hours after onboarding.

Compensation

Compensation is output-based and paid per qualifying task, with an expected rate of $60 to $120 per hour.

Application Process

• Submit an application and complete the screening questions.
• Complete an approximately 30-minute AI interview.
• Proceed through hiring manager review.
• By continuing the application, you acknowledge the candidate terms and privacy policy.