Hardware Engineer - AI Trainer

DataAnnotation; Markham; Remote; CAD 201,000 - 286,000; Full time

Job summary

DataAnnotation is seeking an experienced Electrical Engineer to guide frontier AI models in evaluating real electrical engineering tasks. The role leverages your design judgment, debugging, and hardware experience to teach AI systems to reason about circuits, power stages, and physical constraints.

You will design engineering problems, test them with frontier AI models, and critique model outputs with rigorous reasoning. Remote-first environment with global collaboration.

Qualifications

• Fluency in English (native or bilingual level).
• 2+ years of industry experience in circuit or electronics engineering.
• Background in electrical/electronics engineering or closely related discipline.
• Strong command of circuit analysis and design tradeoffs.
• Ability to articulate why an answer is wrong, not only that it is.
• Comfort working with AI tools or ability to pick them up quickly.

Responsibilities

• Design challenging, realistic engineering problems for frontier AI models.
• Run problems through models and judge output to professional standard.
• Compare model versions on identical prompts and evaluate performance.
• Critique model-derived derivations, schematics, and calculations with written rationale.
• Flag concrete failures with evidence and correct any errors.

Skills

English fluency

Electrical/Electronics Eng

Circuit analysis

AI tools familiarity

Communicate decisions

Education

Bachelor’s degree in EE / related

Tools

None specified

Job description

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 $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k 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.