Handshake AI
Handshake AIVerified listing
Remote

PCB Design Expert - Remote Contract Work

125/hr
Remote
Posted September 17, 2026
Part-Time
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Listing checked September 18, 2026 · pay as published by Handshake AI

Overview

Handshake AI seeks engineers who know LibrePCB, KiCAD, Ngspice, or Qucs-S to join an AI research effort as per-hour contractors. The work centers on judging AI-generated electronics content, writing domain prompts, and reviewing model answers that touch PCB layout, schematic capture, and embedded hardware design. You choose your hours and work from any location, with no minimum weekly commitment. Projects arrive based on availability, so this fits alongside other commitments.

What You'll Do7

  • 1Develop prompts that test AI models on PCB layout, schematic capture, and EDA workflows.
  • 2Review AI responses for technical accuracy in electronics design tasks.
  • 3Provide written feedback that explains where model output fails or succeeds.
  • 4Use LibrePCB, KiCAD, Ngspice, or Qucs-S to verify design claims in model output.
  • 5Flag gaps in AI reasoning about component selection, circuit behavior, or signal integrity.
  • 6Collaborate with AI research teams through async channels.
  • 7Adapt prompts and evaluation criteria as project needs shift.

Requirements6

  • 1At least one year of hands-on work with PCB design tools.
  • 2Direct experience using KiCAD, LibrePCB, Ngspice, or Qucs-S.
  • 3Ability to assess schematic capture and PCB layout decisions.
  • 4Comfort with async work alongside research teams.
  • 5Familiarity with embedded hardware design concepts.
  • 6Strong written communication for detailed feedback.

Who Should Apply

The ideal candidate has at least a year of real PCB work in KiCAD, LibrePCB, Ngspice, or Qucs-S and can explain layout or simulation choices in clear writing. This role suits engineers who already hold another job or study schedule and want part-time, remote project work. People without direct EDA tool experience will struggle, since the tasks require judging model output against practical electronics knowledge. Candidates often score low when they list PCB familiarity without naming specific tools or projects. Another common miss is applying without examples of async written feedback, because the job depends on clear text reviews.

Salary Insight

The listed rate is $125.00 per hour. That sits at a premium level for part-time AI training and annotation work, and it matches the specialized PCB and EDA knowledge this project expects. Pay comes as per-hour contract work, so total earnings depend on project availability and the hours you take on.

Pay and demand for Hardware & Embedded Systems roles

Aggregated

Typical pay

$80/hour

This role

$125/hr

Most Hardware & Embedded Systems roles pay $70–$100 per hour. This role's pay sits above that range.

Based on 103 similar roles that publish pay · 10 publish only a top rate; those count at the rate they gave

Typical rangeMedian payThis role

Rates shown per hour. Yearly and monthly pay converted; one-time fees and non-USD pay are not included.

Live similar roles
108
Listed in last 30 days
71
Remote
97%

Hiring most right now: micro1 (46) · Handshake AI (21) · Mercor (20)

Most requested skills · share of roles

  • electrical engineering
    16%
  • technical writing
    16%
  • matlab
    14%
  • Rust
    14%

Figures from Hardware & Embedded Systems roles live on NearSkill when this page loaded. A role can close before you apply, so check the listing itself.

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Location

Typeremote
LocationRemote
Eligible countriesUnited States
This is a remote position

Compensation

$125/hr

Required Skills

pcb designkicadlibrepcbngspicequcs-sedaschematic capturepcb layoutembedded hardware designcircuit simulationllm evaluationprompt developmentai research

Application Tip

Name the exact EDA tools you have used, such as KiCAD, LibrePCB, Ngspice, or Qucs-S, and attach a short sample of written technical feedback you have given on a schematic or simulation. Quantify your experience, for example one year or more, and mention any async collaboration with research or engineering teams. That evidence helps reviewers see you can both practice PCB design and critique AI output.

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