Astronomy Quality Assurance Lead

The work

You will lead quality checks for astronomy and astrophysics AI training work. The role covers AI-generated content, trainer submissions, and quality assurance reviews, with a focus on scientific accuracy, physical reasoning, mathematical correctness, terminology, units, clarity, formatting, and review rules.

You will give clear written feedback, raise serious issues, communicate with trainers and quality reviewers, and help improve how remote expert contributors work. You will also support contributor follow-up, onboarding, documentation, and ongoing quality improvements.

• Review explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning.
• Check trainer and quality assurance submissions against project guidelines and detailed rubrics.
• Identify incorrect physical assumptions, wrong units, flawed calculations, invented facts, misleading explanations, and oversimplified conclusions.
• Track recurring quality issues and help align contributors on updated expectations.
• Maintain style guides, FAQs, trackers, examples, honeypots, calibration tasks, and onboarding materials.

What it pays and takes

This is a remote, part-time contractor role for candidates based in the United States. The listing is marked entry level, but the work requires substantial astronomy or astrophysics knowledge and a related degree.

• Pay: Up to $110 per hour.
• Time: 20 or more hours per week.
• Location: United States only; remote work.
• Language: Strong written English.
• Education: A degree in astronomy, astrophysics, physics, space science, planetary science, cosmology, or a closely related field.
• Knowledge: Celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty.
• Experience: Astronomy or astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or a related scientific workflow.
• Preferred background: AI training, data annotation, large language model evaluation, scientific quality assurance, academic review, or rubric-based review.

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 systems that generate and understand text, images, audio, and code. Reviewers check model outputs against expert standards so these systems become more accurate, useful, and reliable.