Engineering / Manufacturing / Technical Operations Evaluator
J
JobgetherEngineering, Manufacturing
United StatesContractSenior
Salary80 - 120 USD per hour
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Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- Microsoft OfficePowerPointGoogle WorkspaceCritical thinking
Requirements
- 5+ years of relevant professional experience in engineering, manufacturing, technical operations, or a closely related discipline.
- Demonstrated practical knowledge of professional engineering or manufacturing environments and the operational processes used to deliver technical outcomes.
- Strong analytical and critical-thinking skills, with the ability to assess technical information for accuracy, completeness, and practical applicability.
- Excellent attention to detail and the ability to identify subtle factual, technical, or presentation-related issues.
- Native or professional fluency in English, with strong written communication skills.
- Highly proficient in Microsoft Office and Google Workspace, particularly PowerPoint and Google Slides.
- Ability to work independently, follow structured evaluation criteria, and provide consistent assessments in a remote environment.
- Strong professional judgment and the ability to communicate technical feedback clearly to a research or evaluation team.
- Advanced degree, such as a Master's degree or higher, is preferred.
Responsibilities
- Evaluate AI-generated documents, spreadsheets, presentations, and other technical work products against defined domain-specific quality standards.
- Apply practical engineering, manufacturing, and technical-operations expertise to assess the accuracy, rigor, completeness, and relevance of generated outputs.
- Identify factual, technical, aesthetic, formatting, and presentation issues that could affect the quality or usefulness of an AI-generated deliverable.
- Distinguish authentic professional-level judgment from generic, theoretical, or insufficiently rigorous responses.
- Provide clear, structured, and actionable written feedback explaining errors, weaknesses, and opportunities for improvement.
- Apply evaluation rubrics consistently while using professional judgment to assess nuanced or complex technical scenarios.
- Contribute to the development of higher-quality AI systems by identifying patterns in model performance and communicating domain-specific insights.
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