Remote Electrical Engineer & AI Trainer for Hardware AI

DataAnnotation; Des Moines (IA); Remote; USD 55,000 - 172,000; Full time

Benefits offered by this job

Flexible remote work

Project-based work

Job summary

DataAnnotation is seeking an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring your engineering judgment, built from years of designing, debugging, and shipping hardware, while we provide engineering problems the models cannot yet solve on their own.

You will design challenging problems, run them through frontier AI models, compare versions, critique model outputs, and document the reasoning behind your calls to

Qualifications

• 2+ years of industry experience in circuit or electronics engineering.
• Fluency in English (native or bilingual level).
• Background in electrical/electronics engineering or related discipline.
• Strong ability to defend design tradeoffs and system-level decisions.

Responsibilities

• Design challenging, realistic engineering problems for AI models.
• Run problems through frontier AI models and judge outputs to a professional standard.
• Compare model versions on identical prompts to identify strengths and weaknesses.
• Critique model-generated derivations, schematics, and component choices with written rationale.
• Flag concrete failures with evidence and ensure accuracy of results.

Skills

Circuit design

Electronics engineering

RF/mixed-signal

Control systems

AI tools familiarity

Power systems

English proficiency

Education

Bachelor’s degree or equivalent

Tools

AI tools

Job description

DataAnnotation is seeking an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring your engineering judgment, built from years of designing, debugging, and shipping hardware, while we provide engineering problems the models cannot yet solve on their own.

You will design challenging problems, run them through frontier AI models, compare versions, critique model outputs, and document the reasoning behind your calls to