Mechanical Engineering

Alignerr Corp.; Adelaide; Remote; AUD 69,000 - 117,000; Part time

Job summary

Alignerr is seeking a Mechanical Engineering AI Trainer to design challenging, multi-domain problems and author expert-level solutions that rigorously test AI performance in fluid dynamics, thermodynamics, and structural mechanics. Remote, hourly contract with flexible 10–40 hours per week to fit your schedule.

You will audit AI reasoning, verify CAD logic and physics proofs, and provide precise feedback to improve model accuracy, safety, and compliance with ASME/ISO standards.

Qualifications

• Advanced degree in mechanical/aerospace engineering or closely related field.
• Strong foundations in solid, fluid mechanics and thermodynamics.
• Excellent written communication of complex technical material.

Responsibilities

• Design advanced engineering problems spanning multiple domains to test AI.
• Author ground-truth, step-by-step technical solutions for AI learning.
• Audit AI-generated CAD logic, thermodynamic proofs and material specs.
• Document and report errors to improve model quality and safety.

Skills

Deep domain knowledge

Solid mechanics

Fluid mechanics

Thermodynamics

CAD/CAM

Technical communication

Education

Master's degree in Mechanical Engineering

PhD in Mechanical Engineering

Tools

SolidWorks

MATLAB

ANSYS

Job description

Mechanical Engineering AI Trainer

About The Role

We're partnering with the world's leading AI research labs to build smarter, more technically rigorous AI — and we need mechanical engineers to make it happen. As a Mechanical Engineering AI Trainer, you'll put your deep domain expertise to work by designing complex engineering problems, authoring expert-level solutions, and auditing AI reasoning across fluid dynamics, thermodynamics, structural mechanics, and more.

This is a unique opportunity to work at the frontier of AI development — no prior AI experience needed. If you can spot a flawed stress analysis or an energy conservation violation, you already have what it takes.

• Organization: Alignerr
• Type: Hourly Contract
• Location: Remote
• Commitment: 10–40 hours/week

What You'll Do

• Design Advanced Engineering Problems — Create challenging, multi-domain problems spanning FEA, heat transfer, kinematics, fluid mechanics, and material science to rigorously test AI performance.
• Author Ground-Truth Solutions — Write precise, step-by-step technical solutions that serve as the gold standard benchmark for AI learning and evaluation.
• Audit AI-Generated Technical Content — Review AI outputs including CAD logic, thermodynamic proofs, and material specifications for accuracy, safety, and compliance with standards such as ASME and ISO.
• Refine AI Reasoning — Identify and document logical errors in AI-generated reasoning — from incorrect force distributions to energy conservation failures — and provide structured feedback to improve model quality.

Who You Are

• Advanced Degree — Master's (pursuing or completed) or PhD in Mechanical Engineering, Aerospace Engineering, or a closely related field.
• Deep Domain Knowledge — Strong foundations in solid mechanics, fluid mechanics, thermodynamics, CAD/CAM, or manufacturing processes.
• Technical Communication — Able to explain complex physical phenomena and mathematical derivations clearly and concisely in writing.
• Precision-Oriented — High attention to detail when reviewing mathematical derivations, unit conversions, and physical system constraints.
• No AI experience required — your engineering expertise is what matters.

Nice to Have

• Prior experience with data annotation, quality evaluation, or technical review workflows.
• Proficiency with engineering tools such as SolidWorks, MATLAB, or ANSYS.
• Familiarity with evaluating AI-generated code or simulation workflows.

Why Join Us

• Work on cutting-edge AI projects alongside top research labs and engineers worldwide.
• Fully remote and flexible — set your own hours and work on your own schedule.
• Freelance autonomy with meaningful, intellectually stimulating work.
• Contribute directly to improving how AI understands and reasons through real engineering problems.
• Potential for ongoing work and contract extension.