Remote Electronics Engineer & AI Reasoning Trainer

DataAnnotation

Arizona

Remote

USD 55,000 - 172,000

Full time

7 hours ago
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Job summary

DataAnnotation is seeking an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring years of designing, debugging, and shipping hardware to guide AI reasoning about circuits and physical constraints.

This is a new area focused on teaching AI to reason about circuits, systems, and physical constraints. You will design challenging problems, run them through AI models, compare versions, and critique the reasoning with

Qualifications

  • 2+ years of circuit or electronics engineering experience.
  • Background in electrical/electronics engineering.
  • Strong circuit analysis and design tradeoffs.
  • Ability to defend decisions with rationale; articulate why an answer is wrong.

Responsibilities

  • Design challenging, realistic engineering problems for AI evaluation.
  • Run those problems through frontier AI models and judge output to a professional standard.
  • 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.

Skills

Circuit design
Electrical engineering
Circuit analysis
AI tooling familiarity
English fluency
2+ years experience
Bachelor's degree preferred

Education

Bachelor's degree

Job description

DataAnnotation is seeking an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring years of designing, debugging, and shipping hardware to guide AI reasoning about circuits and physical constraints.

This is a new area focused on teaching AI to reason about circuits, systems, and physical constraints. You will design challenging problems, run them through AI models, compare versions, and critique the reasoning with

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