Automotive Engineering QA & AI Trainer

About OpenTrain

OpenTrain is the #1 platform for finding and building careers in AI training and data labeling. We connect people with flexible, remote work that helps shape how AI systems learn and behave. Creating an OpenTrain account is free and lets you discover projects, build a profile, and apply in minutes.

About AI training work

AI training (also called data labeling or human feedback) is the human side of building AI. Contributors annotate data, rate model outputs, and create the examples that modern models learn from. This work is remote, often part-time or contract-based, and accessible to specialists and generalists alike — it’s a direct way to influence cutting-edge AI behavior.

Role overview

We’re hiring an Automotive Engineering QA / AI Trainer to review and audit prompts and model responses on vehicle systems topics. You will verify calculations and engineering rationale, rate outputs against rubrics, and draft improved prompts and solutions with constructive feedback. This is a contract, part-time role (less than 20 hours/week).

Pay: USD $40 per hour. Employment type: Contractor, Part-time. Work is remote but some location restrictions apply (see Requirements). Work focuses on text-based review and engineering validation using practical Python when needed.

• Label types: Programming/coding checks, evaluation/rating, prompt-response writing (SFT), QA/RLHF, Q&A, text generation.
• (project will provide access and instructions).

What you’ll do (day-to-day)

You will examine model prompts and responses across topics such as vehicle dynamics, powertrain and electrification, control systems, embedded/ECU/CAN, electronics, ADAS/functional safety, and manufacturing/quality. Your focus will be accuracy, clarity, and engineering rigor.

• Verify engineering calculations, units, notation, and derivations; flag and correct errors.
• Assess design rationale, trade-offs, assumptions, and conformance to standards.
• Rate responses against detailed QA rubrics and provide written, constructive feedback.
• Draft improved prompts and example solutions to help the model and future contributors.
• Perform quick Python-based checks, small notebooks, or basic scientific-stack validations as needed.

Requirements & qualifications

Must-haves and strong preferences are listed below. We will verify qualifications during the interview and require passing an AI interview + QA test before work begins.

• 3+ years professional experience in automotive engineering or a closely related field (vehicle systems, powertrain, controls, electronics, or similar).
• Bachelor’s degree required; Master’s or PhD strongly preferred.
• Practical Python skills for analysis and validation (quick checks, notebooks, basic scientific stack).
• Able to evaluate step-by-step engineering reasoning, equations, design trade-offs, and standards; meticulous about notation and units.
• Strong written English and clear, concise technical writing.
• Comfortable switching topics quickly and following detailed QA rubrics; prior LLM QA / RLHF / SFT experience is a plus.

Location, equipment, and screening

This role is remote and open worldwide except for a list of restricted locations. Candidates must have a reliable computer and internet connection and be able to complete the platform interview and QA test.

Restricted locations — candidates present in any of these should not proceed: Iran, Cuba, North Korea, Syria, Sudan, Venezuela, Myanmar; Switzerland; China, Taiwan; Kenya; Armenia, Israel, Kazakhstan, UAE, Netherlands, Serbia, Kyrgyzstan, Turkey, Uzbekistan, Belarus, Russia, Ukraine, Abkhazia, South Ossetia; US states: Alaska, Arkansas, California, Connecticut, Delaware, Georgia, Hawaii, Illinois, Indiana, Kansas, Louisiana, Maine, Maryland, Massachusetts, Nebraska, Nevada, New Hampshire, New Jersey, New Mexico, Ohio, Oregon, Tennessee, Utah, Vermont, Washington, West Virginia; Antarctica, Aruba, Åland Islands, Saint Barthélemy, Bonaire, Sint Eustatius and Saba, Bouvet Island, Cocos (Keeling) Islands, Democratic Republic of the Congo, Cook Islands, Christmas Island, Western Sahara, Falkland Islands (Malvinas), French Guiana, Guadeloupe, South Georgia and the South Sandwich Islands, Heard Island and McDonald Islands, British Indian Ocean Territory, Northern Mariana Islands, Martinique, New Caledonia, Norfolk Island, Niue, French Polynesia, Saint Pierre and Miquelon, Pitcairn, Réunion, Saint Helena, Ascension and Tristan da Cunha, Svalbard and Jan Mayen, Sint Maarten (Dutch part), French Southern Territories, Tokelau, United States Minor Outlying Islands, Holy See, Virgin Islands (British), Wallis and Futuna, Mayotte.

How the process works

Apply through OpenTrain with your CV and a brief summary of relevant automotive experience and Python work. If shortlisted, you’ll complete a screening interview and an engineering QA test that includes sample prompt/response reviews and a short validation exercise in Python.

Successful candidates are onboarded as contractors, given project-specific rubrics and labeling software access, and begin work on batches of text-based tasks. Tasks are completed remotely and rated per-project; you will receive feedback and calibration sessions as needed.

• Time commitment: under 20 hours/week, flexible scheduling.
• Compensation: $40/hour (PAY_PER_HOUR).
• Employment: Contractor, Part-time.