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Civil Engineering Expert

Role overview

Qualifications

  • 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

Responsibilities

  • 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

Key facts

Hard skills

Other skills

  • Problem Solving
  • Detail Oriented

About the company

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Anyone AI

  • Vocational Training & Bootcamps
  • 11–50
We invest in talent from Latam to bridge the talent gap in AI. Join our AI community: www.anyoneai.com We are AI / ML experts and second-time entrepreneurs, members of the founding team at Deep Vision AI (acquired in early 2020). We've worked with many Fortune 500 companies completing multiple projects in the early days of AI while leveraging remote talent from LatAm. We are VC-backed from day 1 by top global investors like GFC -Global Founders Capital- (investors in Facebook, LinkedIn, Slack, Canva, Trivago, etc), Canvas Ventures (early investor in Coursera), Latitud Fund (the largest community of angel investors for LatAm including investments in QuintoAndar, La Haus, Clara, Platzi, OnTop, Pomelo, etc), among other investors.

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Job description

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

About the role

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.

What you’ll do

  • 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

What we’re looking for

  • 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

Nice to have

  • 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

  

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