Mechanical Engineering AI Trainer

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this role. OpenTrain is the #1 platform for finding and building careers in AI training and data labeling, helping people discover projects, build their profiles, and apply in minutes. Creating an OpenTrain account is free.

• Remote contract work with a flexible schedule
• Part-time commitment of fewer than 20 hours per week
• Hourly compensation ranging from $10 to $45 USD

About AI Training Work

AI training is the human side of building artificial intelligence. Experts create examples, review model outputs, and provide carefully reasoned feedback so advanced systems can produce more accurate and useful results. In this project, your engineering judgment and verified computational work will directly support the development of next-generation AI.

• Contribute to generative AI evaluation and human feedback
• Apply real technical knowledge to challenging model-training tasks
• Work remotely with a flexible part-time structure

The Role

As a Mechanical Engineering AI Trainer, you will help train and evaluate advanced AI models by creating computationally intensive mechanical engineering problems and providing verified, Python-based solutions. The work is suited to an intermediate-level engineering professional or researcher with strong scientific-computing skills.

• Employment type: Part-time contractor
• Time requirement: Fewer than 20 hours per week
• Pay: $10 to $45 USD per hour
• Primary language: Advanced English

What You'll Do

You may develop multi-step engineering problems that require numerical methods, iteration, simulations, and careful validation. You will use Python to create solutions that are technically sound, reproducible, and sufficiently rigorous for evaluating advanced AI models.

• Create computationally intensive mechanical engineering problems
• Develop and verify Python-based engineering solutions
• Perform multi-step calculations and iterative numerical analysis
• Work across thermodynamics, fluid mechanics, and heat transfer
• Address solid mechanics, dynamics and vibrations, and mechanical design
• Cover manufacturing processes and thermal systems where relevant
• Apply modeling and analysis workflows involving CAE, FEA, and CFD concepts

Required Qualifications

You must meet one of the following education and experience paths: a relevant bachelor's degree plus at least one year of relevant work experience, or a master's degree or PhD in a relevant field. Relevant experience for the bachelor's pathway may include mechanical or aerospace engineering practice or research in design, analysis, research and development, manufacturing, simulations, or academic research.

Python proficiency is required, including demonstrable experience with engineering or scientific computing. Advanced English at the C1 level is also required and may be demonstrated through a test score, an English-taught degree, or advanced English use in professional or academic work.

• Relevant fields include mechanical, aerospace, materials, mechatronics or robotics, industrial, manufacturing, and energy systems engineering
• Related qualifying fields include engineering physics, applied physics, applied mathematics, and computational mechanics
• Required Python experience may include NumPy, SciPy, pandas, numerical methods, simulation scripts, or optimization scripts
• Intermediate experience level

Preferred Qualifications

Additional experience is welcome but not required. The strongest candidates may have substantial professional experience or exposure to engineering simulation and analysis environments.

• Three or more years of professional experience in a relevant engineering area
• Experience with thermodynamics, fluids, heat transfer, solid mechanics, dynamics and vibrations, or mechanical design
• Experience in manufacturing, CAD or CAE, FEA, CFD, or thermal systems
• Exposure to ANSYS, Abaqus, COMSOL, OpenFOAM, MATLAB, Simulink, or similar tools
• PE, Chartered Engineer, relevant national licensure, certifications, or clear progress toward licensure

Location Eligibility

The project is listed as worldwide, subject to the following location restrictions. Applicants in the locations below are not eligible.

• Countries: Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine, Switzerland, China, Taiwan, and Kenya
• United States 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, and West Virginia
• Regions and 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 Georg
• Additional restricted regions: Svalbard and Jan Mayen, Sint Maarten (Dutch part), French Southern Territories, Tokelau, United States Minor Outlying Islands, Holy See, British Virgin Islands, Wallis and Futuna, Mayotte
• Additional restrictions: 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, Pana

How to Apply

Create a free OpenTrain account, build your profile around your engineering education and experience, and apply through OpenTrain. Be prepared to demonstrate your Python-based scientific-computing ability and advanced English proficiency if requested.

• Confirm that your education and experience meet one of the required pathways
• Highlight relevant mechanical engineering, simulation, and numerical-analysis work
• Showcase Python projects involving engineering or scientific computing
• Apply for flexible remote AI training work through OpenTrain