Mechanical Engineer - AI Trainer

DataAnnotation; Lincoln (NE); Remote; USD 142,000 - 202,000; Full time

Job summary

DataAnnotation is seeking an experienced Mechanical Engineer to help train AI models by writing hard, verifiable engineering problems and solving them yourself. You will show where today’s AI systems still fall short of a practicing engineer.

Responsibilities include reviewing AI-generated results, validating schemes, and ensuring real-world applicability across CAD, structures, and dynamics. Remote role with strong growth in a fast-developing field.

Qualifications

• 2+ years of professional mechanical engineering experience across design, product development, or manufacturing.
• Bachelor’s degree in mechanical engineering or related field (completed or in progress).
• Ability to write precise, unambiguous engineering problems and worked solutions in fluent English.
• Strong CAD/FEA/analysis tool proficiency and fundamentals in mechanics of materials.

Responsibilities

• Write challenging, closed-ended problems from your area of expertise.
• Derive the correct answer, verify it, and write a worked solution.
• Test problems against AI systems and sharpen them for challenge.
• Review AI-generated engineering analysis, designs, and documentation for correctness.
• Review other contributors’ problems and solutions for correctness and rigor.

Skills

Technical writing

Fluent English

Engineering judgment

Attention to edge cases

Education

Bachelor's degree in Mechanical Engineering

Tools

SolidWorks

Fusion 360

Onshape

Creo

NX

CATIA

Inventor

MATLAB

Python

Job description

We’re looking for an experienced Mechanical Engineer to help train AI models. You’ll write hard, verifiable engineering problems drawn from your own specialty, work out the answers yourself, and show us exactly where today’s AI systems still fall short of a practicing engineer.

This is a new and fast-growing area for our company, focused on teaching AI to reason like an engineer. The models can already talk fluently about mechanical engineering. What they can’t yet do reliably is the actual work: size a component against a real load case, catch the failure mode a spec sheet doesn’t mention, read a CAD assembly and tell you what interferes at full travel, or predict what a design change breaks downstream. Your engineering judgment becomes the benchmark those models are measured against.

What you’ll actually do

• Write challenging, closed-ended problems from your area of expertise, built so that solving them requires real engineering reasoning rather than a lookup.
• Derive the correct answer, verify it, and write a worked solution showing how you got there.
• Test your problems against AI systems and sharpen the ones they get right until they challenge the model.
• Review AI-generated engineering analysis, designs, and technical documentation for correctness and real-world applicability.
• Review other contributors’ problems and solutions for correctness, ambiguity, and rigor.

Problems draw on whatever you know best:

• Mechanical design and CAD: geometry, clearances, tolerances, mechanisms, and the effect of design changes.
• Structures and materials: stress, deflection, fatigue, buckling, material selection, and failure analysis.
• Thermal and fluids: heat transfer, thermodynamics, HVAC, pumps and piping, and fluid mechanics.
• Dynamics and controls: vibration, kinematics, rotating machinery, and control systems.
• Manufacturing: DFM/DFA, process selection, GD&T, tolerance stack-ups, and cost and quality trade-offs.

What we look for

• 2+ years of professional mechanical engineering experience in any specialty: design, product development, manufacturing, thermal, structural, automotive, aerospace, HVAC, robotics, energy, or related fields.
• Fluency in the tools of your specialty, such as CAD (SolidWorks, Fusion 360, Onshape, Creo, NX, CATIA, or Inventor), FEA/CFD, or MATLAB/Python for engineering analysis.
• Strong fundamentals across mechanics of materials, dynamics, thermodynamics, heat transfer, fluid mechanics, and manufacturing processes.
• Able to write a precise, unambiguous technical problem and a clear worked solution in fluent written English.
• Meticulous: you check your own work and enjoy finding the edge case that breaks an assumption.
• A bachelor’s degree in mechanical engineering or a related field (completed or in progress).
• Only applicants based in Australia, Canada, Ireland, New Zealand, the United Kingdom, or the United States will be considered for this role.

Compensation

Up to $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income.

About DataAnnotation

DataAnnotation is where 1M+ experts train the world’s leading AI models. Hundreds of millions paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.