Electronics Engineer & AI Model Reviewer (Remote)

DataAnnotation; Colorado; Remote; USD 55,000 - 172,000; Full time

Job summary

DataAnnotation seeks an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring the judgment from years of designing, debugging, and shipping hardware as we teach AI to reason about circuits, systems, and physical constraints.

You’ll design problems, run them through AI models, compare versions, critique derivations, and flag failures with concrete evidence, ensuring accuracy and reliability in tool building.

Qualifications

• 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 and the ability to defend decisions.
• The ability to articulate why an answer is wrong.
• Working comfort with AI tools, or the ability to pick them up quickly.
• Bachelor’s is preferred but not required.

Responsibilities

• Design challenging, realistic engineering problems from your practice.
• Run problems through frontier AI models and judge output against professional standards.
• Compare model versions on identical prompts and assess performance.
• Critique model-generated derivations, schematics, component selections, and calculations with reasoning.
• Flag concrete failures with evidence such as wrong assumptions or unphysical results.

Skills

Circuit analysis

Design tradeoffs

AI tools familiarity

English fluency

2+ years of experience

Education

Bachelor's degree preferred

Tools

AI tooling platforms

Job description

DataAnnotation seeks an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring the judgment from years of designing, debugging, and shipping hardware as we teach AI to reason about circuits, systems, and physical constraints.

You’ll design problems, run them through AI models, compare versions, critique derivations, and flag failures with concrete evidence, ensuring accuracy and reliability in tool building.