Mechanical Engineering

We're partnering with the world's leading AI research labs to build smarter, more technically rigorous AI systems — and we need mechanical engineers to make it happen.

About the role

As a Mechanical Engineering AI Trainer, you'll put your deep domain expertise to work by challenging, auditing, and refining how advanced AI models reason through real engineering problems. This is a rare opportunity to work at the intersection of engineering and artificial intelligence — fully remote, with flexible hours.

Commitment: 10–40 hours/week (flexible), hourly contract.

Responsibilities

• Design Complex Engineering Problems — Craft advanced, domain-specific challenges spanning FEA (Finite Element Analysis), heat transfer, fluid dynamics, kinematics, thermodynamics, and material science to rigorously test AI capabilities.
• Author Ground-Truth Solutions — Develop precise, step-by-step technical solutions and benchmark "golden responses" that AI models learn from and are evaluated against.
• Audit Technical Reasoning — Review AI-generated outputs including CAD logic, thermodynamic derivations, and material specifications for accuracy, safety, and compliance with engineering standards (ASME, ISO, etc.).
• Identify and Correct Reasoning Failures — Spot logical errors such as incorrect force distributions, energy conservation violations, or flawed kinematic assumptions, and provide structured feedback that directly improves AI reasoning.

Requirements

• Highly Educated in the Field — Master's degree (in progress or completed) or PhD in Mechanical Engineering, Aerospace Engineering, or a closely related discipline.
• Deep Domain Knowledge — Strong foundational expertise in one or more of: solid mechanics, fluid mechanics, thermodynamics, CAD/CAM, or manufacturing processes.
• A Clear Technical Communicator — Able to translate complex physical phenomena and mathematical derivations into clear, structured written explanations.
• Precise and Detail-Oriented — Meticulous when reviewing mathematical proofs, unit conversions, boundary conditions, and physical system constraints.

No AI experience required — if you know engineering, we'll handle the rest.

Nice to Have

• Prior experience with data annotation, technical writing, or evaluation systems.
• Proficiency with engineering software such as SolidWorks, ANSYS, or MATLAB.
• Familiarity with AI/ML workflows or large language model evaluation.

Benefits

• Work on the Cutting Edge — Collaborate directly with teams building the most advanced AI models in the world.
• Full Flexibility — Work remotely on your own schedule, fitting the role around your existing commitments.
• Meaningful Impact — Your engineering expertise directly shapes how AI understands and reasons about the physical world.
• Autonomy — No micromanagement. You own your work and deliver with independence.
• Freelance Freedom — Enjoy the perks of contract work: flexibility, variety, and global collaboration.
• Potential for Ongoing Work — High-quality contributors are regularly offered contract extensions.