Mechanical Engineering Subject Matter Expert

$60–100/hrrate as listed

micro1 is contracting mechanical engineers to write, solve, and critique advanced problems across mechanics, thermodynamics, fluids, heat transfer, vibrations, and manufacturing for AI training data. Pay is output-based per accepted task, with rates observed in the $80–100/hr equivalent range and a weekly minimum submission requirement.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

The work

You will be handed engineering problems and AI-generated attempts at them, and asked to decide whether the reasoning holds up. That means working through the analysis yourself — free-body diagrams, energy balances, dimensionless groups, modal assumptions, tolerance stacks — then documenting where the model's chain of reasoning diverges from sound engineering practice. A significant share of tasks involves judgment that textbooks don't cover: whether a proposed geometry is actually manufacturable, whether a stated safety factor is defensible, whether a heat transfer correlation is being applied outside its valid range. Written rationale matters as much as the correct answer; the rationale is the training signal.

What the screen looks for

micro1's process is AI-led and moves quickly — typically an asynchronous conversational interview followed by domain tasks. It probes for specifics rather than credentials: which analyses you personally ran, what the boundary conditions were, what went wrong in production and how you diagnosed it. Vague answers about "leading design efforts" get followed up until they resolve into concrete technical detail. Expect at least one problem where the AI-generated solution is subtly wrong and you must identify the error, explain its consequence, and correct it without over-rewriting. Preferred backgrounds are MS or PhD in Mechanical Engineering, or a BS with 8+ years of hands-on industry work that includes shipping something to production.

Logistics

Fully remote, contractor engagement, largely asynchronous with occasional calibration calls.
Compensation is per accepted task, not hourly; effective rate depends on your speed and first-pass acceptance rate.
A weekly minimum task count applies — this is not a work-whenever arrangement.
Roles fill within roughly 48 hours, and selected experts are expected to submit first tasks 24–48 hours after onboarding.
Project duration is customer-dependent; volume can shift with little notice.

Strong written English is a hard requirement, since the deliverable is prose explanation as much as calculation.

What they look for

remote collaboration
Engineering Mechanics
Thermodynamics
Fluid Mechanics
Heat Transfer
Manufacturing
Vibrations

Before you apply

Would you pass this screen?

Drawn from what this listing actually requires. Answered in your browser — nothing is sent to us, and we do not store your answers.

Do you hold an MS or PhD in Mechanical Engineering, or can you confirm at least 8 years of related full-time professional mechanical engineering experience?
Graduate degree in Mechanical Engineering or equivalent work experience · required
Have you taken a mechanical system or product through to production manufacturing—not purely academic, simulation, or consulting work?
Real-world product or systems development · required
Can you confirm practical experience in at least four of these areas: engineering mechanics, thermodynamics, fluid mechanics, heat transfer, vibrations, or manufacturing (design, analysis, or process)?
Hands-on depth in core mechanical disciplines · required
Is English your native language, or can you confirm professional-level fluency in both written and spoken technical English, validated by past engineering work or formal certification?
English proficiency for technical writing · preferred
Are you able to complete onboarding and submit your first task within 48 hours of being selected for the role?
Immediate availability to start · required

0 of 5 answered

Included with this listing

Interview prep — 11 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: Can the candidate demonstrate depth across the core disciplines listed (mechanics, thermodynamics, fluid mechanics, heat transfer, vibrations, manufacturing) rather than narrow specialization, and do they articulate the reasoning chain clearly enough to teach an AI system?
A strong answer: Describe a specific past project where multiple physics domains were genuinely coupled (e.g., thermal stress in a heat exchanger, or vibration damping in a pump system), name the disciplines involved, explain why each mattered, and show how you validated the solution against real constraints.
Where people lose it: Naming only one discipline, treating the problem as purely analytical without grounding in production realities, or leaving the reasoning implicit instead of spelling out how you integrated different physical effects.