About this opportunity
Confidential lists this STEM Technical Problem Solver for AI Training opportunity in Little Rock Air Force Base, Arkansas. Review the employer’s description below for duties, qualifications and application requirements.
Job description
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.
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.