Astronomer & Space Scientist

If you are an astronomer or space sciences expert with a passion for technical precision, quantitative reasoning, and physics-based problem solving, this opportunity allows you to directly influence how advanced AI systems comprehend and communicate complex space science concepts. You will play a crucial role in evaluating, challenging, and refining state-of-the-art language models on specialized topics within astronomy and space sciences. Your expertise will contribute to enhancing some of the world’s leading AI models and help shape the future landscape of artificial intelligence.

This position is offered by SME Careers, a rapidly growing AI Data Services company and a subsidiary of SuperAnnotate. We provide high-quality training data to many of the largest AI companies and foundation-model research labs globally. While there is no immediate project available for this role, qualified candidates will be among the first contacted for upcoming opportunities. Joining our expert network also grants access to future projects as they arise.

Key Responsibilities

- Evaluate AI-generated responses for scientific accuracy, logical consistency, completeness, and clarity across a range of astronomy and space science topics.
- Challenge language models using realistic scenarios, calculations, and research-style reasoning tasks, ensuring claims are appropriately qualified without overstating certainty.
- Review and refine AI-generated prompts, model answers, and step-by-step solutions, paying close attention to units, assumptions, approximations, and uncertainty.
- Provide structured feedback that identifies conceptual errors, incorrect assumptions, missing constraints, misapplied formulas, unit inconsistencies, or misleading and overconfident statements.
- Assess AI performance on specialized topics such as orbital mechanics (transfer intuition, perturbations, reference frames), stellar and galactic astrophysics (luminosity, magnitudes, spectra, distances), cosmology basics (redshift, expansion, observational constraints), planetary science (thermal balance, atmospheres, surface processes), space physics (plasmas, solar wind, magnetospheres), and data interpretation (signal-to-noise ratio, selection effects, uncertainties, statistics).
- Contribute to defining AI communication standards for scientific content, especially regarding how models express assumptions, uncertainty, and the limits of inference.

Required Qualifications

- A minimum of four years of professional experience in astronomy, astrophysics, planetary science, space physics, heliophysics, cosmology, observational astronomy, mission science or operations, instrumentation, or a closely related space science discipline.
- Deep understanding of core fundamentals relevant to your specialty, including classical mechanics, electromagnetism, radiative processes, stellar and galactic physics, orbital mechanics, coordinate systems, time standards, statistics and uncertainty, and scientific modeling assumptions.
- Strong ability to sanity-check results by verifying orders of magnitude, unit consistency, limiting cases, and error propagation, while responsibly communicating any limitations.
- Bachelor’s degree in physics, astronomy, space science, engineering, or a closely related field is required. A Master’s degree or PhD is strongly preferred.

Preferred Qualifications and Benefits

- Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is highly advantageous.
- Familiarity with scientific and data analysis tools such as Python, NumPy, SciPy, data pipelines, catalog queries, photometry, spectroscopy concepts, or mission datasets is a plus.
- Being part of our expert network offers early access to future projects and the opportunity to collaborate with leading AI and space science professionals.

This role is ideal for experts eager to apply their scientific knowledge to cutting-edge AI development, helping to ensure that AI systems accurately represent and reason about complex scientific domains.