1\. Role Overview
Mercor is collaborating with a leading AI research lab on a project to advance engineering problem-solving at the frontier of artificial intelligence. We are seeking experienced engineers with strong backgrounds in analytical problem design, real-world systems modeling, or competitive engineering problem-solving (university competitions, design challenges, or advanced coursework). The goal of this project is to create novel, rigorous, and multi-step engineering problems that challenge cutting-edge AI models—specifically those that cause the AI to fail or demonstrate reasoning limits—while supporting the improvement and training of advanced AI systems. This is a short-term, high-impact opportunity for engineering professionals eager to apply their deep technical expertise to frontier AI research, with the possibility of project continuation based on performance. ## 2\. Key Responsibilities - Design original, advanced engineering problems that require creative reasoning, multi-domain integration, and precise analytical thinking. - Evaluate AI-generated engineering solutions for technical accuracy, completeness, and adherence to physical and practical constraints. - Identify logical gaps, incorrect modeling assumptions, or computational inaccuracies. - Provide complete, clear, and well-documented solutions and derivations using LaTeX formatting for equations and schematics. - Maintain high standards of technical precision, rigor, and conceptual depth. ## 3\. Required Qualifications Note : Applicants must be proficient in creating and formatting technical documents using LaTeX. You are a strong fit for this project if you have one or more of the following : - Advanced degree (or equivalent experience) in mechanical, electrical, civil, aerospace, or chemical engineering, or a related field. - Experience designing or grading complex analytical or design-focused problems (university level or professional exams). - Participation in or mentorship for engineering design or modeling competitions is preferred(e.g., Formula SAE, Shell Eco-marathon, ASME / IEEE / AIChE contests, robotics challenges, or design sprints). - Research or teaching experience involving applied problem formulation and quantitative modeling. Other qualifications : - Deep understanding of core engineering principles and real-world systems. - Ability to communicate step-by-step reasoning, assumptions, and derivations clearly. - Strong intuition for problem difficulty, structure, and conceptual progression. - Detail-oriented verification of results and internal consistency. ## 4\. More About the Opportunity - Time commitment : Minimum 20 hours / week; up to 40 hours / week available - Duration : Approximately 2 months, with strong potential for extension - Rolling onboarding; start typically within 1–2 days after approval ## 6\. Application Process 1. Submit your resume or CV highlighting your engineering background and relevant accomplishments. 2. Participate in a short interview (20–30 minutes). 3. Complete a brief form outlining your experience with problem design, engineering challenges, or teaching. 4. Selected applicants will receive follow-up steps within a few days.
Remote Engineering Expert (PhD, Master's, or Olympiad Participants) - AI Trainer ($60-$80 per hour) • Tulare, California, US
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