Mechanical Engineering

Alignerr partners with leading AI research teams to build and train cutting-edge AI models. The Mechanical Engineering - AI Data Trainer will design complex mechanical engineering problems, create rigorous solutions for AI benchmarks, and evaluate AI-generated technical logic for accuracy and safety.

Responsibilities:

• Develop Complex Problems: Design advanced mechanical engineering problems across domains like FEA (Finite Element Analysis), heat transfer, kinematics, and material science to test AI performance
• Author Ground-Truth Solutions: Create rigorous, step-by-step technical solutions and 'golden responses' that the AI will use as a benchmark for learning
• Technical Auditing: Evaluate AI-generated CAD logic, thermodynamic proofs, and material specifications for technical accuracy, safety, and adherence to engineering standards (e.g., ASME, ISO)
• Refine Reasoning: Identify logical fallacies in AI reasoning—such as incorrect force distributions or energy conservation violations—and provide structured feedback to improve the model's 'thinking' process

Requirements:

• Advanced Degree: Masters (pursuing or completed) or PhD in Mechanical Engineering, Aerospace Engineering, or a closely related field
• Domain Expertise: Strong foundational knowledge in core areas such as solid mechanics, fluid mechanics, CAD/CAM, or manufacturing processes
• Analytical Writing: The ability to communicate highly technical concepts and complex physical phenomena clearly and concisely in written form
• Attention to Detail: High level of precision when checking mathematical derivations, unit conversions, and physical system constraints
• No AI experience required
• Prior experience with data annotation, data quality, or evaluation systems
• Proficiency in engineering software concepts (e.g., SolidWorks, MATLAB, ANSYS) to evaluate AI-generated code or workflows