Help shape the future of AI by designing challenging civil engineering problems that test and improve reasoning in cutting-edge models.
Location: Remote
Type: Contract / Part-time
Commitment: 20 hours per week
Compensation: Up to 40 USD / hr
Project duration: 2 months, with potential extension
We create high-quality STEM training data for frontier AI models. Our data is used directly in training and evaluation pipelines at leading AI labs to improve model reasoning in technical domains.
We are looking for experts in Civil Engineering to design rigorous, deterministic problems that are genuinely challenging for state-of-the-art AI systems. Each problem must have exactly one verifiable correct answer and be submitted together with a complete, verified solution.
Design advanced civil engineering problems for frontier AI training and evaluation
Create deterministic problems with exactly one correct answer
Write complete, verified solutions and clearly document the reasoning process
Develop problems involving structural analysis, geotechnical engineering, hydraulics, transportation, construction, or infrastructure systems
Create problems that require multi-step engineering reasoning rather than simple formula application
Where relevant, use Python, MATLAB, structural analysis software, or other engineering tools to validate solutions
Ensure all outputs are technically precise, reproducible, and well-written in English
Master’s or PhD in Civil Engineering or a closely related field
Strong research or industry experience in structural, geotechnical, transportation, hydraulic, construction, or infrastructure engineering
Strong quantitative modeling and engineering problem-solving skills
Solid understanding of engineering mechanics, numerical methods, and technical standards
Ability to design original, difficult problems that reflect realistic civil engineering workflows
Excellent attention to detail and technical writing skills in English
Experience with SAP2000, ETABS, STAAD.Pro, PLAXIS, Civil 3D, MATLAB, Python, or similar tools
Background in structural simulation, finite element analysis, infrastructure modeling, or engineering optimization
Experience evaluating technical work, developing assessments, or creating engineering educational content