Astronomy Quality Assurance Lead

About Open Train

Open Train is the #1 platform for finding and building careers in AI training and data labeling. We help people discover specialized projects, build a professional profile, and apply in minutes as they grow experience teaching and evaluating AI.

Creating an Open Train account is free. For this role, Open Train AI is recruiting remote contractors to support expert-led astronomy and astrophysics AI training work.

AI training is the human side of building modern artificial intelligence. People review model outputs, assess reasoning, prepare examples, and provide detailed feedback so AI systems become more accurate, useful, and reliable.

In this role, your astronomy and astrophysics expertise will help evaluate specialized scientific content. Your reviews can improve how AI handles physical reasoning, calculations, terminology, uncertainty, and explanations.

Open Train is seeking an Astronomy Quality Assurance Lead to review AI-generated astronomy and astrophysics content, trainer submissions, and QA work. You will assess scientific accuracy, physical reasoning, mathematical correctness, terminology, unit handling, clarity, formatting, and adherence to detailed rubrics.

The role also includes written feedback, issue escalation, communication with trainers and QA contributors, documentation, onboarding support, and process improvement across remote expert teams. This is a remote contractor and part-time role for candidates currently located in the United States, with a commitment of 20+ hours per week.

• Employment type:
  
  Contractor and part-time
• Location:
  
  United States only
• Time requirement: 20+ hours per week
• Hourly rate:
  Up to $110 per hour
• Working language:
  English

You will combine subject-matter expertise with structured quality review. Your work will help identify scientific errors, clarify expectations for contributors, and improve the consistency of astronomy and astrophysics training data.

• Review astronomy and astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning.
• Check trainer and QA submissions against project guidelines and detailed review rubrics.
• Identify recurring quality issues and communicate updates to align contributors on expectations.
• Maintain style guides, FAQs, trackers, examples, honeypots, calibration tasks, and onboarding materials.
• Support activation follow-up and quality workflow improvements for remote expert contributors.
• Provide clear written feedback and provide

This role requires strong astronomy or astrophysics knowledge and the ability to evaluate scientific content precisely. A degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field is required.

You should be able to distinguish correct scientific reasoning from incorrect assumptions, inconsistent calculations, unsupported claims, and misleading simplifications. Strong written English is required for precise feedback and team coordination.

• Degree in astronomy, astrophysics, physics, space science, planetary science, cosmology, or a closely related field.
• Deep knowledge of celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty.
• Ability to identify incorrect physical assumptions, wrong units, flawed calculations, hallucinated facts, misleading explanations, and oversimplified conclusions.
• Strong written English communication skills.
• Ability to review astronomy, physics, or scientific content against rubrics.
• Experience with astronomy or astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or related scientific workflows.

Experience in AI training, data annotation, large language model evaluation, scientific QA, academic review, or rubric-based review is a strong plus. Familiarity with these workflows can help you communicate quality standards and support remote contributors effectively.

• AI training or data annotation experience.
• Large language model evaluation experience.
• Scientific quality assurance or rubric-based review experience.
• Academic review, teaching, science communication, data analysis, or observatory workflow experience.

AI training and data‑labeling work is a growing part of the technology industry, with opportunities for specialists who bring expertise in fields such as astronomy and physics. Open Train helps you build a durable profile around that experience while discovering projects that match your skills.