LLM Analytical Quality Analyst

You will help improve large language models by creating and evaluating analytical scenarios, reviewing model answers, checking claims through online research, and writing precise annotations. The work combines language comprehension, logical reasoning, data interpretation, content review, and structured feedback.

• Answer questions involving data interpretation, trends, logical reasoning, basic arithmetic, and quantitative constraints.
• Create scenarios that reveal weaknesses in model reasoning.
• Read and summarize content, then divide larger materials into clear logical blocks.
• Research information online and validate claims in written content.
• Review model responses, identify errors, and provide correct answers with clear explanations.
• Write constructive feedback focused on accuracy, reasoning, and formatting.

What It Pays and Takes

This is a part-time contractor role with a commitment of 20 or more hours per week. No pay rate is provided in the role details.

• Location: Open worldwide for remote work.
• Language: Fluent English reading and writing.
• Work setup: Reliable desktop or laptop and internet connection.
• Required skills: Research, analysis, data interpretation, logical reasoning, clear writing, and careful attention to text accuracy and formatting.
• Work style: Ability to work independently in a remote setting.
• Helpful background: A bachelor's degree or current undergraduate study in engineering, literature, journalism, communications, arts, statistics, or a related field.
• Helpful experience: Quality assurance, data annotation, content review, professional writing, editing, translation, or research analysis.
• Useful tools and knowledge: Excel, Google Suite, logical reasoning, and basic arithmetic.

How It Works

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

About AI Training Work

AI training is the human work behind modern artificial intelligence, including writing examples, reviewing model answers, and explaining why one response is better than another. People with strong reasoning, language, research, or subject knowledge help make AI systems more accurate and useful.