Engineering Experts — Planning AI Project
vetto • Remote • Posted 22 days ago
Education
Any
Type
Pay Rate
$60/task
Posted
22d ago
About this Role
About Vetto
Vetto is a global platform that connects top-tier professionals to strategic Artificial Intelligence projects around the world. Our mission is to build trust, quality, and long-term value within the AI ecosystem, for both exceptional talent and companies operating at the forefront of technology.
About the project
We're recruiting engineering experts to review and improve real-world technical scenarios used to train AI planning assistants in an educational context. The AI model will act as a tutor — explaining engineering topics, solving problems step by step, and teaching concepts to university-level students. Your job is to think like a senior engineer and educator: map decision trees, identify alternative hypotheses, justify conclusions with concrete data, and ensure the reasoning is both technically sound and clear enough to teach.
Who can apply
Mechanical, Civil, Electrical, Chemical, Industrial, or Aerospace Engineers. Any engineer with hands-on experience diagnosing problems, designing solutions, or running technical analyses. Professionals who routinely make data-driven decisions in their field. Final-year undergraduate engineering students with a solid technical foundation are also welcome to apply.
Compensation
If approved in the project, payment will be US$ 60 per approved task, converted and paid in your local currency. Each task takes approximately 80 minutes, which corresponds to an effective rate of about US$ 45 per hour.
Selection & Case Instructions
In this application, you will answer questions following the instructions below and complete a test case. If selected, you will be invited to review real engineering case scenarios as part of the project. ‼️ AI is not allowed. If we spot AI use, we'll block the application. ⚠️ This application form must be completed entirely in English or Portuguese. For the reasoning case, present a real technical engineering problem you diagnosed or solved — a failure, root cause analysis, dimensioning decision, process issue, etc. You may anonymize it. We are not evaluating whether your conclusion was right. We are evaluating how you think. The case is structured in 4 parts: Part 1 — The Problem: describe the technical problem and what data or information you had available at the start. Part 2 — Your Journey: describe your reasoning in 3 steps. For each step, explain what you analyzed or decided and what specific measurement, calculation, test, or evidence drove that decision. Part 3 — Discarded Alternatives: for each of the 3 steps, list at least 2 hypotheses you considered but ruled out and explain what concrete data eliminated each one. "It wasn't the case" is not a valid answer. Part 4 — Conclusion: describe the final diagnosis or solution and how the evidence you gathered led to it. Also highlight 1–2 key insights — the most important findings or turning points in your reasoning: a piece of data that confirmed your direction, a detail that ruled out a strong alternative, or a non-obvious observation that most people would have missed.
Case Example
⚠️ The following is just an illustrative example. Your application should include more detail, specific data points, and thorough reasoning for each discarded alternative. Part 1 — The Problem A building wall developed visible cracks after heavy rain. The owner reported it had been getting worse over 3 months. Part 2 — Your Journey Step 1: Inspected foundation drainage and found water accumulation near the base — water presence only after rain suggested drainage failure rather than structural issue.
Step 2: Excavated around the foundation and confirmed soil erosion undermining one corner — localized erosion pattern pointed to a specific drainage origin point.
Step 3: Waterproofed the foundation and regraded the soil to redirect water flow — erosion was contained and structure still sound, no need for full replacement. Part 3 — Discarded Alternatives Step 1 — Alternative 1: Structural overload / Ruled out by: no recent changes to the building load. Step 1 — Alternative 2: Material defect / Ruled out by: cracks only appeared after rain season, not from construction. Step 2 — Alternative 1: Poor original construction / Ruled out by: building was 12 years old with no prior issues. Step 2 — Alternative 2: Tree roots / Ruled out by: no vegetation near the affected area. Step 3 — Alternative 1: Full foundation replacement / Ruled out by: erosion was localized, structure confirmed sound by inspection. Step 3 — Alternative 2: Sealing the cracks only / Ruled out by: treating the symptom without addressing the drainage cause would reproduce the problem. Part 4 — Conclusion Root cause was poor drainage causing progressive soil erosion. After waterproofing and regrading, no new cracks appeared in the following 2 months. Key insights: The most critical finding was that cracks only appeared after rain season — this single observation immediately ruled out structural and material causes and focused the entire investigation on drainage. The second turning point was confirming the erosion was localized: it meant a targeted fix was sufficient and avoided an unnecessary full foundation replacement.
Requirements
- Must be eligible to work in Remote
- Fluent proficiency in English (Written & Verbal)
- Reliable high-speed internet connection
- Bachelor's degree or equivalent professional experience
- Demonstrated expertise in STEM
Eligible Languages
Fluent proficiency in English or Portuguese
Compensation Analysis
Vetto is a global platform that connects top-tier professionals to strategic Artificial Intelligence projects around the world. Our mission is to build trust, quality, and long-term value within the AI ecosystem, for both exceptional talent and companies operating at the forefront of technology.
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Frequently Asked Questions
How do I get started?
Review the hiring process above and follow the steps outlined. Each platform has different requirements, so make sure you meet the eligibility criteria before applying.
Is this work legitimate?
Yes. All platforms listed on aitrainer.work are legitimate and pay reliably. However, always verify payment methods and read reviews before committing significant time.
Is this just labeling data?
No. This is closer to academic research. You will likely be writing or verifying complex proofs, solving advanced equations, or checking the logic of a model's step-by-step reasoning. The goal is to teach AI systems to reason deeply in your field.
Do I need a PhD?
For the highest pay tiers in this category, a PhD (or current enrollment) is usually expected. However, the most important factor is your ability to pass the domain assessment. If you can solve the problems, the degree is secondary.
Is the work continuous?
Work in niche fields is often project-based. A specific "campaign" (e.g., training a model on Quantum Mechanics) might last for a few weeks. It is best to treat this as a high-paying fellowship or grant rather than a permanent daily job.