Manufacturing Expert (English)

OpenTrain AI, Inc.

United States

Remoto

USD 80.000 - 113.000

Tempo pieno

8 ore fa
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Vantaggi offerti da questo lavoro

Remote work
Flexible hours
Asynchronous work

Descrizione del lavoro

OpenTrain AI, Inc. is seeking experienced manufacturing professionals to create realistic challenges and evaluate AI responses for accuracy, practicality, and industry standards.

This remote, contract role offers flexible, asynchronous work and pays $70 per hour for 20+ hours per week. You will transform manufacturing knowledge into questions on production planning, quality control, lean manufacturing, and process optimization, then provide detailed feedback to improve model performance.

Competenze

  • Bachelor's degree or equivalent professional experience in a relevant field.
  • Background in manufacturing operations, production management, or industrial engineering.
  • Strong analytical, written, and verbal communication skills.
  • Experience across different production settings and process improvement is helpful.

Mansioni

  • Create manufacturing challenges on production planning, quality control, lean manufacturing, process optimization, and related topics.
  • Review AI-generated answers for accuracy, applicability of principles, and industry standards.
  • Write detailed feedback explaining errors and sound reasoning to improve model responses.
  • Collaborate with manufacturing experts to set question difficulty and keep materials challenging.

Conoscenze

Analytical skills
Written communication
Verbal communication
Attention to detail
Experience in manufacturing operations

Formazione

Bachelor's degree in manufacturing engineering, industrial engineering, mechanical engineering, operations management, or related field

Strumenti

Industry 4.0 familiarity
IIoT knowledge
Lean Six Sigma (certification preferred)

Descrizione del lavoro

Create manufacturing challenges and assess AI responses for accuracy, practical value, and industry standards. Remote contract work pays $70 per hour for 20+ hours per week.

The work

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.
What it pays and takes
  • 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.
About AI training work

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.

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