Astronomer & Space Scientist at SME Careers

If you are an astronomer or space sciences expert who thrives on technical precision, quantitative reasoning, and physics-based problem solving, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex space science concepts. We are looking for specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network.

Responsibilities

Evaluate AI-generated responses for scientific accuracy, logical soundness, completeness, and clarity across astronomy & space science topics.
Challenge language models with realistic scenarios, calculations, and “research-style” reasoning tasks (without overclaiming certainty).
Review and refine AI-generated prompts, model answers, and step-by-step solutions (units, assumptions, approximations, uncertainty).
Provide structured feedback identifying conceptual errors, bad assumptions, missing constraints, misused formulas, unit mistakes, or misleading/overconfident claims.
Assess performance on topics such as: Orbital mechanics (transfer intuition, perturbations basics, reference frames) Stellar/galactic astrophysics (luminosity/flux, magnitudes, spectra, distances) Cosmology basics (redshift, expansion concepts, observational constraints) Planetary science (thermal balance, atmospheres basics, surface processes) Space physics (plasmas, solar wind, magnetospheres) depending on specialty Data interpretation (SNR, selection effects, uncertainties, statistics)
Help shape AI communication standards for scientific content, especially how models state assumptions, uncertainty, and limits of inference.

Requirements

4+ years of professional experience in astronomy, astrophysics, planetary science, space physics, heliophysics, cosmology, observational astronomy, mission science/operations, instrumentation, or a closely related space science domain.
Deep knowledge of core fundamentals relevant to your specialty, such as classical mechanics, electromagnetism, radiative processes, stellar/galactic physics, orbital mechanics, coordinate systems, time standards, statistics/uncertainty, and scientific modeling assumptions.
Strong ability to sanity-check results (orders of magnitude, unit consistency, limiting cases, error propagation) and communicate limitations responsibly.
Bachelor’s degree required (physics/astronomy/space science/engineering or closely related); Master’s/PhD strongly preferred.
Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus.
Familiarity with tools/workflows like Python/NumPy/SciPy, data pipelines, catalog queries, photometry/spectroscopy concepts, or mission datasets is a plus.

Responsibilities

Evaluate AI-generated responses for scientific accuracy, logical soundness, completeness, and clarity across astronomy & space science topics.
Challenge language models with realistic scenarios, calculations, and “research-style” reasoning tasks (without overclaiming certainty).
Review and refine AI-generated prompts, model answers, and step-by-step solutions (units, assumptions, approximations, uncertainty).
Provide structured feedback identifying conceptual errors, bad assumptions, missing constraints, misused formulas, unit mistakes, or misleading/overconfident claims.
Assess performance on topics such as: Orbital mechanics (transfer intuition, perturbations basics, reference frames) Stellar/galactic astrophysics (luminosity/flux, magnitudes, spectra, distances) Cosmology basics (redshift, expansion concepts, observational constraints) Planetary science (thermal balance, atmospheres basics, surface processes) Space physics (plasmas, solar wind, magnetospheres) depending on specialty Data interpretation (SNR, selection effects, uncertainties, statistics)
Help shape AI communication standards for scientific content, especially how models state assumptions, uncertainty, and limits of inference.

Requirements

4+ years of professional experience in astronomy, astrophysics, planetary science, space physics, heliophysics, cosmology, observational astronomy, mission science/operations, instrumentation, or a closely related space science domain.
Deep knowledge of core fundamentals relevant to your specialty, such as classical mechanics, electromagnetism, radiative processes, stellar/galactic physics, orbital mechanics, coordinate systems, time standards, statistics/uncertainty, and scientific modeling assumptions.
Strong ability to sanity-check results (orders of magnitude, unit consistency, limiting cases, error propagation) and communicate limitations responsibly.
Bachelor’s degree required (physics/astronomy/space science/engineering or closely related); Master’s/PhD strongly preferred.
Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus.
Familiarity with tools/workflows like Python/NumPy/SciPy, data pipelines, catalog queries, photometry/spectroscopy concepts, or mission datasets is a plus.