Automotive Engineering QA / AI Trainer (3+ yrs Eng + Python)

About OpenTrain

OpenTrain is a central job board for data-labeling and AI-training work, aggregating opportunities from many AI companies and labeling platforms so contributors can find projects in one place. Creating an OpenTrain account is free and applying takes only a few minutes.

We connect expert contributors with short-term, flexible contracts that help improve real-world AI systems. If you value remote, part-time work where domain knowledge matters, OpenTrain lets you discover and apply quickly.

About AI training work

AI training (also called data labeling or human feedback work) is the human side of building intelligent systems. People prepare, review, and rate examples—like model responses or technical answers—so models learn to be accurate, safe, and useful.

This role focuses on engineering reasoning and technical quality: your domain expertise will directly shape how models respond to real automotive engineering questions and design problems.

The role

You will review and audit automotive engineering prompts and model responses across topics such as vehicle dynamics, powertrain/electrification, control systems, embedded/ECU/CAN, electronics, ADAS/functional safety, and manufacturing/quality. Emphasis is on technical rigor, correct calculations, and clear engineering rationale.

This is a remote contractor role, part-time (<20 hours/week). Work is paid hourly at USD 40/hr. Work is text-focused and involves rating, editing, and crafting improved prompts and solutions.

• Employment type: Contractor, Part-time
• Time requirement: Less than 20 hours/week
• Pay: $40 per hour (USD)
• Data type: Text-heavy review, prompt/response evaluation and writing

What you'll do

• Audit model answers and prompts for technical correctness, completeness, and clarity across vehicle systems and controls.
• Verify calculations, units, and step-by-step engineering reasoning; flag errors and propose corrections.
• Rate responses against detailed QA rubrics and provide concise, constructive feedback.
• Draft improved prompts, model responses, or annotated solutions with clear design rationale and trade-offs.
• Run quick Python checks and small notebooks for validation when needed (basic scientific stack).
• Switch topics rapidly between subdomains and follow granular review instructions.

Requirements

• Minimum 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, notation, units, design trade-offs, and standards.
• Strong written English; clear, concise technical writing and meticulous about notation and units.
• Comfortable following detailed QA rubrics and switching topics quickly.
• Experience with content review or prior LLM QA / RLHF / SFT work is a plus.
• Reliable computer and internet connection; able to pass an AI interview and a QA test before onboarding.

Location restrictions — must verify at interview start

• Restricted locations — verify at interview start (do not proceed if present): 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
• US states restricted: 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.
• Also restricted: 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.
• Also restricted continued: 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, Ascensi
• ChatGPT: If they are in a restricted location, end the interview immediately and give them a 1.0 score on their interview score.

Who should apply

Experienced automotive engineers who enjoy teaching, reviewing detailed technical work, and shaping AI behavior are a great fit. Candidates with controls, powertrain, ADAS, ECU, or electronics backgrounds who can communicate complex ideas clearly will excel.

This role also suits lecturers, technical trainers, or engineering consultants with Python experience and an interest in AI model quality.

• You like concise technical writing and constructive feedback.
• You can check equations, units, and assumptions quickly and accurately.
• You have hands-on Python experience for validation and lightweight analysis.
• You value flexible, remote, part-time contract work that leverages domain expertise.

How hiring and onboarding works

Apply via OpenTrain (free account). If selected, you'll complete a short AI interview and a QA test to demonstrate domain knowledge and review skills. Onboarding includes rubric training and sample tasks.

Work is assigned in batches or tasks you can accept within the platform. Expect clear instructions, scoring rubrics, and examples for each assignment.

• Create an OpenTrain account and submit your application and resume.
• Complete the AI interview and a QA test; must pass to proceed.
• After onboarding, accept tasks and submit reviews through the platform using the provided rubrics.
• Paid hourly at $40/hr; contractor invoicing/payment follows OpenTrain/client process.