Create and verify realistic electrical engineering problems, writing clear prompts and reproducible Python solutions. This worldwide contract role pays $15 to $50 per hour and requires an electrical engineering degree plus relevant experience.
The work
You will create original computational problems in electrical engineering and write the solutions. Each problem should reflect a realistic engineering situation, with clear documentation that another person can follow and reproduce.
You will use Python and scientific libraries to solve and check your work. Topics may include system design, optimization, control, and power systems, using realistic constraints and engineering workflows.
- Write both the problem prompt and its solution.
- Use Python-based scientific libraries for mathematics, engineering, verification, and simulation.
- Cover varied electrical engineering topics, including system design, optimization, control, and power systems.
- Make solution explanations clear, detailed, and reproducible.
- Evaluate and refine technical content used to train AI systems.
What it pays and takes
This is an intermediate, part-time contractor role. The work is open worldwide, but you must be fluent in English at C1 level or higher.
- Pay: $15 to $50 per hour, with a listed rate of $40 per hour.
- Time: Less than 20 hours per week.
- Work arrangement: Part-time contract work.
- Location: Worldwide.
- Education: Bachelor's degree or higher in electrical engineering or a closely related field.
- Experience: At least two years of professional or teaching experience in relevant electrical engineering topics.
- Required skills: Python for mathematics and engineering.
- Helpful additional experience: MATLAB, R, C, SQL, or domain-specific engineering libraries.
How it works
Apply on OpenTrain. The employer reviews applications there.
About AI training work
AI training work uses examples created and reviewed by people to help artificial intelligence systems produce better results. Your engineering problems, solutions, and checks give AI models reliable technical material to learn from, which is why subject-matter experience matters.