Mechanical Engineer

In this hourly, remote contractor role, you will review AI-generated engineering solutions and/or generate expert Mechanical Engineering content, evaluating reasoning quality and step-by-step problem-solving while providing crisp written feedback. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify methodological or conceptual errors; fact-check assumptions; write high-quality explanations and model solutions; and rate and compare multiple responses based on correctness and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your mechanical engineering expertise directly helps improve the world’s premier AI models by making their technical reasoning more accurate, reliable, and clearly explained.

Your profile

• Bachelor’s degree (or higher) in Mechanical Engineering, Aerospace Engineering, or Engineering Physics (Thermo/Heat Transfer/Fluids/Statics-Dynamics/Differential Equations).
• Strong, confident fundamentals in mechanics, thermodynamics, fluid mechanics, applied physics, engineering math, and system modeling.
• Comfortable evaluating technical solutions for correctness, methodology, units/dimensional consistency, assumptions, and physical plausibility with high attention to detail.
• Able to clearly explain reasoning and corrections in writing; Minimum C1 English proficiency.
• Experience applying basic design principles (requirements, constraints, margins, trade-offs) in real engineering contexts.
• Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
• Previous experience with AI data training/annotation or technical reviewing is strongly preferred.

Key responsibilities

• Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects.
• Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance.
• Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases.