Mechanical Design Engineer - AI Trainer

DataAnnotation; Aurora (CO); Remote; USD 103,000 - 172,000; Full time

Benefits offered by this job

Flexible, remote work

Job summary

DataAnnotation is seeking an experienced Mechanical Engineer to craft challenging AI-training problems rooted in real engineering practice. You’ll derive, verify, and document worked solutions, setting benchmarks for AI reasoning against practical constraints.

You’ll tackle mechanical design, structures, thermal, dynamics, and manufacturing topics using CAD and analysis tools to ensure rigor and uncover edge cases. Remote-friendly with US/Canada/Australia options.

Qualifications

• 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 CAD tools and engineering analysis software (e.g., CAD, FEA/CFD, MATLAB/Python).
• Bachelor’s degree in mechanical engineering or a related field (completed or in progress).
• Ability to write precise, unambiguous technical problems and worked solutions in fluent written English.

Responsibilities

• 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.

Skills

CAD tools

FEA/CFD

MATLAB/Python

Engineering analysis

Education

Bachelor's degree in mechanical engineering or related field

Tools

SolidWorks

Fusion 360

Onshape

Creo

NX

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.