Manufacturing AI Training Expert

Turn practical manufacturing knowledge into realistic questions and case studies, then review AI-generated answers for accuracy and usefulness.

• Create challenges about production planning, quality control, lean manufacturing, process optimization, supply chain management, equipment maintenance, safety, and related topics.
• Check whether AI responses apply manufacturing principles, best practices, and industry standards correctly.
• Write detailed feedback that points out errors, explains sound reasoning, and helps improve model responses.
• Work with manufacturing and technical experts to set question difficulty and keep the material challenging and educational.

• Pay: $70 per hour.
• Hours: 20+ hours per week. The engagement is remote, flexible, and asynchronous.
• Location: Remote, but applicants must be based in an eligible country. The role is not open worldwide.
• Language: Fluency in English.
• A bachelor's degree in manufacturing engineering, industrial engineering, mechanical engineering, operations management, or a related field is required, or equivalent professional experience.
• Required experience: Background in manufacturing operations, production management, or industrial engineering, plus strong knowledge of manufacturing processes and systems.
• You should have strong analytical, written, and verbal communication skills and close attention to detail.
• Helpful background includes experience in different production settings, process improvement, manufacturing technology, or industry publications. Lean Six Sigma certification, a professional engineering license, or familiarity with Industry 4.0, IIoT, and technology-driven manufacturing can also help.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

OpenTrain helps people find AI training work and build a profile for future opportunities. AI training uses human-written examples and expert feedback to help AI models learn; manufacturing specialists are paid to create realistic challenges and judge whether answers reflect sound production practice.