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Automotive Engineering AI Trainer and QA Reviewer

Review and improve AI prompts and responses across vehicle dynamics, powertrain, controls, embedded systems, ADAS, and manufacturing. This worldwide contract pays $40 per hour for less than 20 hours per week.

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OpenTrain AI

Generative AI & RLHF

100% Remote Hourly · $40/hr

$40/hr

Compensation

Worldwide

Eligibility

Entry

Experience

Oct 1, 2025

Posted

Open worldwide

The Work

You will review and audit prompts and AI-generated responses about automotive engineering. The work includes checking technical accuracy, calculations, design reasoning, clarity, and rigor.

You will rate responses against set rubrics and write improved prompts or solutions with useful feedback.

  • Review topics such as vehicle dynamics, powertrain and electrification, control systems, embedded systems, ECU and CAN, electronics, ADAS and functional safety, and manufacturing and quality.
  • Verify calculations and assess whether the design rationale is technically sound.
  • Evaluate question-and-answer content, generated text, coding content, and model responses.

What It Pays and Takes

This is a part-time contractor role listed as entry level, but it requires substantial professional automotive engineering experience. Work is available worldwide for people who can work in English.

  • Pay: $40 per hour.
  • Time: Less than 20 hours per week.
  • Work arrangement: Part-time contract work.
  • Location: Worldwide.
  • Language: Strong written English.
  • Required experience: At least 3 years of professional experience in automotive engineering or a closely related field.
  • Required technical skill: Python.
  • Preferred background: A master's degree or PhD.
  • Helpful experience: Teaching, lecturing, training, or previous large language model quality assurance or RLHF work.

How It Works

Apply on OpenTrain. The employer reviews applications there.

About AI Training Work

AI training work is the human review and feedback that helps models produce more useful and accurate answers. Experienced specialists are needed to check technical reasoning, identify mistakes, and show models what strong responses look like.

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