Electrical Engineering AI Evaluation Expert

You will help improve AI systems by creating realistic electrical engineering problems and reviewing their answers. Your work should reflect real design, testing, and field practice across electrical engineering.

The contract is remote and asynchronous. You will work independently and provide clear written feedback on technical content.

• Create expert-level engineering problems and scenarios based on real design, testing, and field work.
• Review AI-generated responses for technical accuracy and practical feasibility.
• Judge whether responses match how electrical engineering work is done in practice.
• Write structured feedback that identifies issues and supports better model performance.

What it pays and takes

This is ongoing, flexible, part-time contract work that can be completed alongside another role. There is no set schedule or minimum hour requirement in the role description.

• Pay: Up to $120 per hour for completed work.
• Work arrangement: Remote, asynchronous, part-time contract work.
• Location: You must currently live in the United States.
• Language: English.
• Experience: At least two years of hands-on electrical engineering industry experience.
• Education: An MS or PhD in electrical, electronics, or computer engineering, or a BS in electrical engineering with strong industry experience.
• Technical depth: Power systems, microgrids, high-voltage engineering, semiconductors, chip design, EDA, embedded systems, digital signal processing, RF, or a related area.
• Working style: Strong written communication, careful attention to detail, and independent judgment.
• Helpful tools: MATLAB/Simulink, Python, SPICE, PSCAD, ETAP, PSS/E, Cadence, Synopsys, Altium, KiCad, Verilog/SystemVerilog, or comparable EDA and simulation tools.
• Helpful background: Experience at an established electrical engineering or hardware employer.

How it works

Apply on OpenTrain with your resume, then complete the application on the hiring site.

About AI training work

AI training is the human work behind systems that generate and understand content. Experts create examples, review model responses, and explain what is accurate or useful so AI systems can improve.

Electrical engineering expertise matters because strong evaluations depend on real methods, constraints, and decisions from the field.