Electronics Engineer & AI Trainer — Remote

DataAnnotation; Idaho; Remote; USD 55,000 - 172,000; Part time

Benefits offered by this job

Flexible schedule

Remote-friendly

Project-based opportunities

Job summary

DataAnnotation is seeking an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. Your judgment, your standard for what counts as a correct answer, and the written rationale behind them shape the next generation of engineering tools.

Remotely contribute to creating and testing problems, critique model outputs, and compare model versions on identical prompts.

Qualifications

• Fluency in English (native or bilingual).
• 2+ years of industry experience in circuit or electronics engineering.
• Background in electrical engineering, electronics engineering, or related discipline.
• Strong command of circuit analysis and design tradeoffs; defend decisions.

Responsibilities

• Design challenging, realistic engineering problems from your practice.
• Run those problems through frontier AI models and judge outputs against standards.
• Compare two model versions on identical prompts and call which performed better.
• Critique model-generated derivations, schematics, component selections, and calculations, and write the reasoning behind your call.
• Flag concrete failures with evidence: wrong assumptions, sign and unit errors, unphysical results, invalid topologies, fabricated datasheet values, or off-brief interpretation.

Skills

Circuit analysis

AI tool fluency

Problem solving

English fluency

Education

Bachelor’s degree

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. Your judgment, your standard for what counts as a correct answer, and the written rationale behind them shape the next generation of engineering tools.

Remotely contribute to creating and testing problems, critique model outputs, and compare model versions on identical prompts.