Electronics Engineer - AI Trainer

DataAnnotation; Sachsenburg; Remote; EUR 49.000 - 153.000; Vollzeit

Benefits dieser Stelle

Flexible work

Remote projects

Zusammenfassung

DataAnnotation is looking for an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring the judgment you have built over years of designing, debugging, and shipping hardware.

This role focuses on teaching AI to reason about circuits, systems, and physical constraints. You’ll design problems, test them with models, critique results, and justify each decision with clear, evidence-based rationale.

Qualifikationen

• Fluency in English (native or bilingual).
• 2+ years of industry experience in circuit or electronics engineering.
• Bachelor’s in electrical/electronics engineering or related discipline preferred.

Aufgaben

• Design challenging, realistic engineering problems.
• Run problems through frontier AI models and judge outputs.
• Compare two model versions and identify better performance.
• Critique model-derived derivations, schematics, and calculations with justification.
• Flag concrete failures with evidence and clear rationale.

Kenntnisse

Fluent English

Circuit engineering

Ausbildung

Bachelor's in Electrical Engineering

Jobbeschreibung

DataAnnotation is looking for an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring the judgment you have already built over years of designing, debugging, and shipping hardware. We bring engineering problems the models cannot yet solve on their own.

This is a new and growing area for our company, focused on teaching AI to reason correctly about circuits, systems, and physical constraints. Your engineering judgment, your standard for what counts as a correct answer, and the written rationale behind them become the signal that shapes the next generation of engineering tools.

What you’ll actually do

• Design challenging, realistic engineering problems from your own practice: a circuit to specify, a control loop to stabilize, a power stage to size.
• Run those problems through frontier AI models and judge the output against your professional standard.
• Compare two model versions on identical prompts and call which performed better, and where each fell short.
• 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.

Problems draw on whatever you know best:

• Analog, RF, and mixed-signal circuits.
• Electromagnetics and antennas.
• Control and systems.
• Devices and materials.
• Signal processing and photonics.
• Power and energy systems.

Roles this fits

Common backgrounds: Electrical Engineer, Power Engineer, Systems Engineer.

What we look for

• Fluency in English (native or bilingual level).
• 2+ years of industry experience in circuit or electronics engineering.
• Background in electrical engineering, electronics engineering, or a closely related discipline.
• Strong command of circuit analysis and design tradeoffs, and the ability to defend component-level and system-level decisions.
• The ability to articulate why an answer is wrong, not only that it is.
• Working comfort with AI tools, or the ability to pick them up quickly.
• A current, in-progress, or completed Bachelor’s is preferred but not required.
• Only applicants based in Australia, Canada, Ireland, New Zealand, the United Kingdom, or the United States will be considered for this role.

Compensation

Up to $40 – $125+/hr depending on task difficulty and specialization. Many contributors add $10k–$100k+ a year; some make it their full-time income.

About DataAnnotation

DataAnnotation is where 100k+ experts train the world’s leading AI models. $150M+ paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.