Mechanical Engineering AI Trainer — Python Required

About OpenTrain

OpenTrain is the #1 platform for building careers in AI training and data labeling. We connect skilled contributors with cutting-edge projects that shape how modern AI systems behave. Creating an OpenTrain account is free and opens access to flexible, remote contract work.

Why AI training matters

AI training (also called data labeling or human feedback) is the human side of building artificial intelligence: people create examples, rate model outputs, and provide high-quality solutions that models learn from. This work is remote-friendly, often flexible and part-time, and puts you on the front lines of how state-of-the-art systems are shaped.

• Flexible, remote work you can do from anywhere outside the specified exclusions
• Accessible roles range from entry-level to specialist technical work; this role is specialist-level
• Direct impact on model correctness and safety through high-quality, verified solutions

The role

As a Mechanical Engineering AI Trainer you will create and evaluate computationally intensive mechanical engineering problems and provide verified Python-based solutions used to train and assess advanced AI models. Work focuses on accurate, multi-step numerical problem design and solution verification across engineering topics.

• Contract, part-time work (less than 20 hours/week)
• Data type: TEXT; label types: EVALUATION_RATING and RLHF
• You will produce problem statements, stepwise solutions, and evaluation ratings for model outputs

What you'll do

Your day-to-day tasks involve designing multi-step engineering problems and writing robust Python solutions that use numerical methods, iteration, or simulation scripts. You will also evaluate model responses against your solutions and provide ratings and feedback for RLHF/evaluation workflows.

• Create detailed mechanical engineering problems (thermodynamics, fluids, heat transfer, solid mechanics, dynamics, vibrations, mechanical design, manufacturing processes)
• Write verified Python solutions using scientific libraries (NumPy/SciPy/pandas) and numerical methods
• Design and check calculation workflows that mirror CAE/FEA/CFD reasoning and engineering best practices
• Rate and annotate model outputs, providing clear corrective feedback for training pipelines

Requirements

You must meet one of the education/experience paths below and demonstrate strong English and Python skills to qualify.

• Education + experience: Bachelor's degree in a relevant field plus 1+ year of relevant engineering practice or research OR a Master’s/PhD in a relevant field (mechanical, aerospace, materials, mechatronics/robotics, manufacturing, energy systems, engineering physics, applied math, computational mech
• Python (required): demonstrable experience using Python for engineering/scientific computing (e.g., NumPy, SciPy, pandas; numerical methods; simulation/optimization scripts)
• English: advanced/professional level (C1). Proof via test score, English-taught degree, or evidence of advanced English use in professional/academic work
• Preferred: 3+ years professional experience in thermodynamics, fluids, heat transfer, solid mechanics, dynamics/vibrations, CAD/CAE, FEA, CFD, or related areas
• Nice to have: experience with CAE/FEA/CFD tools (ANSYS, Abaqus, COMSOL, OpenFOAM), MATLAB/Simulink, or professional credentials (PE/Chartered Engineer or progress toward licensure)

Location, eligibility, and exclusions

This role is remote and open worldwide except for the following ineligible locations. Please confirm you are not located in any excluded country, state, or territory before applying.

• Ineligible countries: Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine, Switzerland, China, Taiwan, Kenya
• Ineligible USA 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
• Ineligible territories/regions: Antarctica, Aruba, Åland Islands, Saint Barthélemy, Bonaire/Sint Eustatius/Saba, Bouvet Island, Cocos (Keeling) Islands, Democratic Republic of the Congo, Cook Islands, Christmas Island, Western Sahara, Falkland Islands, French Guiana, Guadeloupe, South Georgia and th
• Additional exclusions: Afghanistan, American Samoa, The Bahamas, Curaçao, Czechia/Czech Republic, Côte d'Ivoire/Ivory Coast, Equatorial Guinea, Eritrea, Eswatini/Swaziland, Ethiopia, Ghana, Greece, Guatemala, Guernsey, Hong Kong, Lebanon, Macao, Mauritania, Montserrat, Nicaragua, Pakistan, Panama, S

Compensation, schedule, and commitments

This is a contractor, part-time role with flexible hours. Expect to work less than 20 hours per week and manage your schedule within project deadlines.

• Pay structure: hourly (PAY_PER_HOUR)
• Rate range: $10–$45 per hour, with a top hourly rate of $45
• Employment types: Contractor, Part-time

How to apply and next steps

If you meet the education/experience and Python/English requirements, apply through OpenTrain with a CV and short summary of relevant projects. Highlight Python examples (scripts or repositories) and engineering problems you've solved or simulated.

Selected candidates will be asked to complete a short skills verification exercise that includes problem creation, a Python solution, and an explanation of your approach.

• Prepare: CV, short portfolio or GitHub links showing Python engineering work, and evidence of English proficiency (if available)
• Expect a practical assessment focusing on problem design, numerical methods, and code correctness