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Job description
About the Role
This contract role is geared toward mechanical engineers who want to contribute to the development of advanced AI systems. You’ll work with leading AI research teams to push language models toward more accurate reasoning about physical systems and engineering principles.
The work focuses on testing whether AI can handle complex mechanical concepts correctly, including fluid dynamics, thermodynamics, structural mechanics, and mechatronics. Your expertise will help surface errors, validate technical outputs, and improve the quality of model responses.
Role Details
- Organization: Alignerr
- Engagement type: Hourly contract
- Work mode: Remote
- Weekly commitment: 10 to 40 hours
What You’ll Be Doing
- Building challenging, discipline-specific engineering problems that examine AI reasoning across FEA, heat transfer, kinematics, materials science, and related areas.
- Creating accurate, step-by-step reference solutions that can be used as ground truth for model training and evaluation.
- Reviewing AI-generated outputs such as CAD reasoning, thermodynamics derivations, and materials specifications for correctness, safety, and alignment with standards like ASME and ISO.
- Spotting and documenting reasoning flaws, including incorrect force distribution, broken energy balance, and unsupported assumptions, then turning that into structured feedback for model improvement.
Candidate Profile
The role is best suited to professionals with advanced academic training in mechanical engineering, aerospace engineering, or a closely related field. A master’s degree in progress or completed, or a PhD, is expected.
You should have strong knowledge of core mechanical engineering areas such as solid mechanics, fluid mechanics, thermodynamics, CAD/CAM, or manufacturing processes. Clear written communication and careful attention to technical detail are important, especially when checking derivations, units, boundary conditions, and system constraints.
No previous experience in AI training or annotation is required.
Preferred Background
- Exposure to data annotation, quality review, or technical assessment workflows.
- Hands-on use of tools such as SolidWorks, MATLAB, or ANSYS.
- Experience from research, academia, or technical writing.
Why Join
- Fully remote work with a flexible schedule that can fit around other commitments.
- Direct involvement with advanced AI development and leading research labs.
- An intellectually engaging way to apply mechanical engineering expertise.
- Firsthand insight into how large language models are trained and evaluated.
- Independence to choose when and how much you work.
- Potential for contract renewal based on performance.