Validation Engineer (AI Training)

DataAnnotation; Australia; Remote; AUD 202,000 - 288,000; Full time

Benefits offered by this job

Flexible hours

Weekly payouts

Remote work

Job summary

DataAnnotation is seeking an experienced Validation Engineer to craft challenging, closed-ended engineering problems drawn from your area of expertise. You will derive answers, write worked solutions, and test problems against AI systems to sharpen model performance.

Responsibilities include reviewing AI-generated analyses and ensuring real-world applicability, plus critiquing others’ contributions for accuracy and rigor. Remote, contract role with flexible hours.

Qualifications

• 2+ years of professional mechanical engineering experience in any specialty.
• Able to write precise, unambiguous technical problems and clear worked solutions in fluent English.
• Fluent written English for technical problem statements.

Responsibilities

• Write challenging, closed-ended problems from your area of expertise.
• Derive correct answers and provide worked solutions showing the reasoning.
• Test problems against AI systems and refine them for robustness.
• Review AI-generated analyses and designs for correctness and real-world applicability.
• Review other contributors’ problems and solutions for accuracy and rigor.

Skills

Mechanical engineering fundamentals

Attention to edge cases

Precise problem writing

Education

Bachelors in mechanical engineering or related field

Tools

CAD tools (SolidWorks, Fusion 360, Onshape, Creo, NX, CATIA, Inventor)

FEA/CFD

MATLAB/Python for analysis

Job description

Overview

We're looking for an experienced Validation 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.

Overview

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.

Roles this fits

Common backgrounds: Validation Engineer, Test Engineer, Reliability Engineer.

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.

Hourly rate up to $125+ / hour

Commitment Flexible hours

Type Independent contractor

Payouts Weekly