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Mechanical Engineering AI Trainer — Python Required

Create and verify Python-based solutions for computational mechanical engineering problems used to train and evaluate AI models. Part-time contract role (less than 20 hrs/week) requiring a relevant BSc+1yr or MSc/PhD, advanced English (C1), and strong Python skills; pay up to $45/hr.

OpenTrain AI

Generative AI & RLHF

100% Remote Hourly · $10–$45/hr

$10–$45/hr

Compensation

Worldwide

Eligibility

Intermediate

Experience

Dec 12, 2025

Posted

Open worldwide

Interested in this role?

Create a free OpenTrain account and apply in minutes.

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. Create a free account, build a profile, and join projects where contributors directly shape how state-of-the-art AI systems behave.

About AI training work

AI training (data labeling / human feedback) is the human side of building modern AI. Contributors prepare and evaluate examples—text, code, audio, or simulations—that models learn from, often on flexible, remote schedules.

This project focuses on mechanical-engineering content: you’ll craft rigorous engineering problems and verified Python solutions that teach models to reason about simulations, multi-step calculations, and analysis workflows.

The role

We’re hiring Mechanical Engineering AI Trainers to produce and evaluate computationally intensive engineering problems and verified Python-based solutions. Work centers on creating accurate, reproducible multi-step calculations and numerical workflows that models will learn from and be evaluated against.

  • Contract, part-time role: less than 20 hours per week.
  • Work type: creating problem prompts, writing Python solutions, and evaluating model outputs (evaluation rating / RLHF tasks).
  • Expected domains: thermodynamics, fluid mechanics, heat transfer, solid mechanics, dynamics & vibrations, mechanical design, manufacturing, and CAE/FEA/CFD concepts.

What you'll do

  • Design multi-step engineering problems suitable for model training and evaluation.
  • Implement verified Python solutions and reproducible scripts (NumPy/SciPy/pandas or similar) for numerical methods, iteration, or simulation workflows.
  • Provide clear explanations, intermediate steps, and verification for each solution so model reviewers can evaluate correctness.
  • Evaluate model responses and rate outputs per provided guidelines (EVALUATION_RATING and RLHF tasks).
  • Optionally reference CAE/FEA/CFD workflows or simulation concepts when relevant, without requiring licensed software output.

Requirements

  • Education: BSc in a relevant field plus 1+ year relevant experience OR an MSc/PhD in a relevant field (mechanical, aerospace, materials, mechatronics, manufacturing, energy systems, engineering physics, applied math, computational mechanics).
  • Experience (if BSc): 1+ year in mechanical/aerospace engineering practice or research (design, analysis, R&D, manufacturing, simulations, or academic research).
  • Preferred experience: 3+ years professional experience in thermodynamics, fluids, heat transfer, solid mechanics, dynamics/vibrations, mechanical design, manufacturing, CAD/CAE, FEA, CFD, or thermal systems.
  • Python (required): demonstrable experience using Python for engineering/scientific computing (e.g., NumPy/SciPy/pandas; numerical methods; simulation or optimization scripts).
  • English (required): Advanced English (C1). Proof via test score, English-taught degree, or evidence of advanced English use in professional/academic work.
  • Nice to have: exposure to CAE/FEA/CFD tools (ANSYS, Abaqus, COMSOL, OpenFOAM), MATLAB/Simulink, or progress toward professional licensure (PE/Chartered).

Location & eligibility

This is a worldwide remote contract opportunity, but candidates from specific countries, territories, and U.S. states are not eligible for this posting.

  • Not eligible (countries): Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar, Russia, Belarus, Palestine, Switzerland, China, Taiwan, Kenya.
  • Not eligible (additional countries/regions): 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, Ni
  • Not eligible (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.
  • Not eligible (territories/regions): 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,

Pay & time commitment

This is hourly pay (PAY_PER_HOUR). Projects for this role range up to $45.00 USD per hour (hourly range listed: $10–$45 USD/hr). Expect less-than-20-hours-per-week assignments and flexible scheduling typical of part-time contractor work.

  • Employment type: Contractor, Part-time.
  • Hourly pay range: $10–$45 USD per hour; top rate listed $45 USD/hr.
  • Typical weekly time commitment: less than 20 hours per week.

How it works

Apply through your OpenTrain account and complete any required screening tasks or qualification tests. Accepted contributors receive project instructions and evaluation rubrics and submit Python solutions and ratings per guidelines.

Expect iterative feedback: solutions and ratings are reviewed for accuracy and consistency; clear, reproducible code and explanations help accelerate acceptance and future work.