Design original civil/computational engineering problems and verify reproducible solutions using Python to create high-quality training data for generative models. Part-time contract (20+ hrs/week), up to $50/hr; requires a Civil Engineering degree, 2+ years relevant experience, and strong written E
About OpenTrain
OpenTrain is the #1 platform for building careers in AI training and data labeling. We connect skilled contributors with projects that teach AI systems—work that shapes how state-of-the-art models behave and improves real-world AI outcomes.
We hire contractors directly for focused, remote projects. Joining OpenTrain means you’ll work on meaningful technical data and content used by researchers and engineers across the industry while keeping flexible, remote hours.
About AI training work
AI training (data labeling/annotation) is the human-driven process for creating the examples and evaluations that modern models learn from. This role creates high-quality problem statements and verified solutions used for text generation, supervised fine-tuning, and evaluation tasks.
Contributors in this field often work remotely on part-time contracts, applying domain expertise to produce reproducible, well-documented artifacts that directly improve model accuracy and safety.
The role
You will design original, realistic civil/computational engineering problems and produce fully verified solutions. Each item must reflect real engineering workflows—analysis, optimization, numerical methods, iterative solutions, or simulation-style calculations—and be validated with reproducible Python code using common numerical libraries.
Deliverables include clear problem statements, step-by-step solution documentation, and verified final answers with accompanying Python validations (NumPy, Pandas, SciPy or equivalent). Accuracy, clarity, and reproducibility are essential.
What you'll do
- Create original civil/computational engineering problems that mirror real professional or research tasks.
- Write concise, unambiguous problem statements suitable for model training and human evaluation.
- Produce fully worked solutions with clear reasoning and step-by-step calculations.
- Validate results using Python (NumPy, Pandas, SciPy or similar) and provide code snippets or notebooks showing reproducible verification.
- Document assumptions, approximations, boundary conditions, and any practical engineering constraints used in each problem.
- Format work so it can be used for supervised fine-tuning, text-generation prompts, and evaluation tasks.
Requirements
You must meet every core requirement below; we cannot accept candidates who do not satisfy these prerequisites.
- Degree in Civil Engineering or a closely related field.
- 2+ years of relevant professional, research, or teaching experience in civil/computational engineering.
- Strong written English (C1 or higher) — your CV must be in English and demonstrate proficiency.
- Proficiency in Python for numerical validation (experience with NumPy, Pandas, SciPy or equivalent).
- If your background includes MATLAB, R, C, SQL, Stata or other languages, that is acceptable provided you can perform verification effectively in Python.
- Practical understanding of engineering constraints, approximations, and standard workflows; clear technical communication and documentation skills.
Who should apply
This role is ideal for civil engineers, computational mechanics specialists, or academics with hands-on experience in numerical methods and engineering analysis who enjoy translating technical work into clear, verifiable problem-and-solution pairs.
Applicants should be comfortable writing reproducible Python code and documenting reasoning clearly for use in model training and evaluation.
Hours, pay, and contract
Contract, part-time role with a time expectation of 20+ hours per week. Compensation is hourly and paid in USD.
Rate information from this posting: hourly pay up to $50 USD/hour; posted range $15–$50 USD/hour. Exact rate will be set by OpenTrain per contract.
How to apply & location restrictions
To apply, submit a CV in English that lists your English proficiency level, an email address, and a phone number. Include brief examples of prior engineering problems or code that demonstrate your ability to validate results in Python.
Note: OpenTrain cannot acquire talent located in certain restricted regions. Applicants located in the following places should not apply: Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine, Switzerland, China, Taiwan, Kenya, the listed U.S. states (Alaska, Arkansas, California, Connecticut, Delaware, Georgia, Hawaii, Illinois, Indiana, Kansas, Louisiana, Maine, Maryland, Massachusetts, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, Ohio, Oregon, Tennessee, Utah, Vermont, Washington, West Virginia), and the following territories: Antarctica, Aruba, Åland Islands, Saint Barthélemy, Bonaire, Sint Eustatius and Saba, Bouvet Island, Cocos (Keeling) Islands, Democratic Republic of the Congo, Cook Islands, Christmas Island, Western Sahara, Falkland Islands (Malvinas), French Guiana, Guadeloupe, South Georgia and the South Sandwich Islands, Heard Island and McDonald Islands, British Indian Ocean Territory, Northern Mariana Islands, Martinique, New Caledonia, Norfolk Island, Niue, French Polynesia, Saint Pierre and Miquelon, Pitcairn, Réunion, Saint Helena, Ascension and Tristan da Cunha, Svalbard and Jan Mayen, Sint Maarten (Dutch part), French Southern Territories, Tokelau, United States Minor Outlying Islands, Holy See, Virgin Islands (British), Wallis and Futuna, Mayotte.
