Astronomy QA Lead - AI Training
Posted date [2026-07-24]
(ID: 48591)
 |
YO IT Consulting specializes in recruiting remote professionals for AI training and data annotation projects with global companies. Based in Abu Dhabi Emirate, United Arab Emirates, the company connects qualified talent worldwide with flexible remote opportunities that contribute to the development and improvement of modern artificial intelligence systems. |
Job Description and Requirements
Astronomy QA Lead - AI TrainingJob Snapshot
Role: Astronomy QA Lead - AI Training
Location: Dubai, United Arab Emirates
Industry: Research
Function: Quality Assurance
Experience: Minimum 3 years in astronomy, astrophysics, research, teaching, observatory work, scientific review, or data analysis
Job Type: Contract - Remote - work from home
Position Overview
Astronomy QA Lead - AI Training in Dubai, United Arab Emirates is a remote Research opportunity focused on improving the scientific accuracy, physical reasoning, mathematical reliability, and observational context of astronomy and astrophysics AI training data. YO IT Consulting is seeking an experienced subject-matter expert who can review AI-generated scientific content, assess trainer and QA submissions, provide precise feedback, and maintain consistent standards across distributed expert teams.
The role covers celestial mechanics, stellar evolution, galaxies, cosmology, planetary science, electromagnetic radiation, spectroscopy, observational astronomy, black holes, and scientific uncertainty.
There is no immediate project assignment. Qualified candidates will join the expert network and receive early consideration when relevant astronomy or astrophysics AI training projects become available.
Job Details
Country: United Arab Emirates
City: Dubai
Industry: Research
Function: Quality Assurance
Salary: 13000-21000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Job Type: Contract - Remote - work from home
Role Context
The Astronomy Quality Assurance Lead will oversee the reliability of scientific material used to train and evaluate advanced artificial intelligence systems. Assignments may include reviewing astrophysical explanations, numerical calculations, observational interpretations, diagrams, comparative analyses, data summaries, and step-by-step scientific reasoning.
The successful candidate will identify incorrect physical assumptions, flawed calculations, inconsistent units, hallucinated facts, misleading explanations, weak sourcing, and physically impossible conclusions. The position also includes contributor coaching, documentation management, onboarding, calibration, and continuous improvement of astronomy-focused review workflows.
Key Responsibilities
* Review astronomy and astrophysics AI training items against detailed project rubrics and scientific quality standards.
* Evaluate scientific accuracy, physical reasoning, mathematical correctness, terminology, clarity, formatting, and instruction compliance.
* Assess explanations involving celestial mechanics, stellar evolution, galaxies, cosmology, planetary systems, and black holes.
* Review calculations related to orbital motion, luminosity, distance, redshift, velocity, radiation, mass, and energy.
* Verify formulas, assumptions, units, constants, intermediate steps, significant figures, and final conclusions.
* Evaluate descriptions of electromagnetic radiation, spectroscopy, photometry, telescope observations, and astronomical instrumentation.
* Review interpretations of observational data, scientific diagrams, light curves, spectra, simulations, and comparative datasets.
* Identify physically impossible scenarios, unsupported assumptions, misleading causal claims, and inaccurate terminology.
* Flag hallucinated discoveries, fabricated observations, false citations, and poorly sourced scientific statements.
* Check whether scientific claims appropriately reflect uncertainty, limitations, measurement error, and competing interpretations.
* Distinguish accepted scientific findings from hypotheses, emerging evidence, and speculation.
* Review explanations involving space science, planetary formation, gravitational systems, cosmic evolution, and observational methods.
* Spot-check submissions completed by researchers, trainers, annotators, educators, science writers, reviewers, and QA contributors.
* Provide precise written feedback explaining each scientific issue and the correction required.
* Escalate recurring, critical, numerically significant, or scientifically misleading quality concerns.
* Communicate updated guidelines, project changes, and astronomy-specific review expectations through Discord and other collaboration tools.
* Respond to contributor questions involving physical assumptions, formulas, units, observational methods, terminology, and rubric interpretation.
* Contact inactive trainers and QAs, encourage participation, document follow-ups, and report availability concerns.
* Create and maintain style guides, FAQs, trackers, quality notes, examples, honeypots, calibration tasks, and onboarding resources.
* Conduct remote onboarding and training sessions for astronomy trainers and reviewers.
* Ensure contributors apply evolving astronomy and astrophysics review standards consistently.
* Analyze recurring quality gaps and recommend practical improvements to scientific review workflows.
* Maintain accurate records of evaluations, contributor feedback, performance patterns, and corrective actions.
Ideal Profile
* Bachelor\'s, Master\'s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related discipline.
* Minimum 3 years of professional experience in astronomy or astrophysics research, teaching, science communication, academic review, observatory work, or scientific data analysis.
* Strong English communication skills for interpreting detailed guidelines and delivering clear written feedback.
* Thorough understanding of celestial mechanics, stellar evolution, galaxies, cosmology, radiation, and planetary systems.
* Strong knowledge of observational astronomy, spectroscopy, photometry, scientific uncertainty, and physical modeling.
* Ability to identify incorrect assumptions, numerical errors, unsupported conclusions, and misleading scientific explanations.
* Familiarity with astronomical datasets, telescope observations, simulations, or observatory workflows is preferred.
* Experience using Python, Jupyter notebooks, LaTeX, scientific visualization tools, or quantitative research methods is advantageous.
* Ability to review equations, calculations, units, constants, and astrophysical interpretations accurately.
* Understanding of research methodology, evidence quality, measurement limitations, and uncertainty communication.
* Experience leading or supporting researchers, educators, science writers, annotators, reviewers, or QA teams is strongly preferred.
* Excellent attention to scientific terminology, numerical detail, physical plausibility, and documentation.
* Confidence using Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
* Experience developing style guides, calibration tasks, onboarding resources, FAQs, and quality documentation is beneficial.
* Familiarity with AI training, data annotation, large language model evaluation, scientific QA, or rubric-based review is advantageous.
* Availability to complete an AI interview, a domain-specific task, and a recruiter interview.
* Comfortable working independently within a fast-moving remote environment.
Skills Set
* Astronomy quality assurance
* Astrophysics
* Celestial mechanics
* Stellar evolution
* Galactic astronomy
* Cosmology
* Planetary science
* Black hole physics
* Electromagnetic radiation
* Spectroscopy
* Photometry
* Observational astronomy
* Telescope data analysis
* Orbital calculations
* Scientific modeling
* Physical reasoning
* Mathematical verification
* Unit validation
* Scientific uncertainty
* Research methodology
* Astronomical datasets
* Python
* Jupyter notebooks
* LaTeX
* Scientific visualization
* Scientific literature review
* Rubric-based assessment
* AI-generated scientific content evaluation
* Large language model evaluation
* Data annotation quality
* Trainer performance monitoring
* Written scientific feedback
* Style guide development
* Calibration task design
* Contributor onboarding
* Remote team coordination
* Discord
* Google Sheets
* Google Docs
* Quality trackers
* Process improvement
Why Join Us
This opportunity allows astronomy and astrophysics professionals to apply advanced scientific expertise within the expanding artificial intelligence sector. The work directly influences how AI systems explain cosmic phenomena, perform astrophysical calculations, interpret observations, handle scientific uncertainty, and avoid physically impossible or unsupported claims.
Qualified specialists will join a flexible remote expert network and receive early consideration for relevant future assignments. The role also provides exposure to international scientific teams, emerging AI evaluation methods, complex astronomy datasets, and quality frameworks used to improve next-generation language models.
About the Company
YO IT Consulting connects scientists, researchers, and domain specialists with remote AI training and scientific quality projects. Operating from Dubai, United Arab Emirates, the company recruits experts worldwide whose professional knowledge helps improve the scientific accuracy, physical reasoning, evidence awareness, and practical reliability of modern artificial intelligence systems.
Job Details
Country: United Arab Emirates
City: Dubai
Industry: Research
Function: Quality Assurance
Salary: 13000-21000
Estimated salary range based on similar jobs in the job city; please confirm the final offer with the employer.
Gender: Any
Candidate Nationality: Any
Job Type: Contract - Remote - work from home
Role Context
The Astronomy Quality Assurance Lead will oversee the reliability of scientific material used to train and evaluate advanced artificial intelligence systems. Assignments may include reviewing astrophysical explanations, numerical calculations, observational interpretations, diagrams, comparative analyses, data summaries, and step-by-step scientific reasoning.
The successful candidate will identify incorrect physical assumptions, flawed calculations, inconsistent units, hallucinated facts, misleading explanations, weak sourcing, and physically impossible conclusions. The position also includes contributor coaching, documentation management, onboarding, calibration, and continuous improvement of astronomy-focused review workflows.
Key Responsibilities
* Review astronomy and astrophysics AI training items against detailed project rubrics and scientific quality standards.
* Evaluate scientific accuracy, physical reasoning, mathematical correctness, terminology, clarity, formatting, and instruction compliance.
* Assess explanations involving celestial mechanics, stellar evolution, galaxies, cosmology, planetary systems, and black holes.
* Review calculations related to orbital motion, luminosity, distance, redshift, velocity, radiation, mass, and energy.
* Verify formulas, assumptions, units, constants, intermediate steps, significant figures, and final conclusions.
* Evaluate descriptions of electromagnetic radiation, spectroscopy, photometry, telescope observations, and astronomical instrumentation.
* Review interpretations of observational data, scientific diagrams, light curves, spectra, simulations, and comparative datasets.
* Identify physically impossible scenarios, unsupported assumptions, misleading causal claims, and inaccurate terminology.
* Flag hallucinated discoveries, fabricated observations, false citations, and poorly sourced scientific statements.
* Check whether scientific claims appropriately reflect uncertainty, limitations, measurement error, and competing interpretations.
* Distinguish accepted scientific findings from hypotheses, emerging evidence, and speculation.
* Review explanations involving space science, planetary formation, gravitational systems, cosmic evolution, and observational methods.
* Spot-check submissions completed by researchers, trainers, annotators, educators, science writers, reviewers, and QA contributors.
* Provide precise written feedback explaining each scientific issue and the correction required.
* Escalate recurring, critical, numerically significant, or scientifically misleading quality concerns.
* Communicate updated guidelines, project changes, and astronomy-specific review expectations through Discord and other collaboration tools.
* Respond to contributor questions involving physical assumptions, formulas, units, observational methods, terminology, and rubric interpretation.
* Contact inactive trainers and QAs, encourage participation, document follow-ups, and report availability concerns.
* Create and maintain style guides, FAQs, trackers, quality notes, examples, honeypots, calibration tasks, and onboarding resources.
* Conduct remote onboarding and training sessions for astronomy trainers and reviewers.
* Ensure contributors apply evolving astronomy and astrophysics review standards consistently.
* Analyze recurring quality gaps and recommend practical improvements to scientific review workflows.
* Maintain accurate records of evaluations, contributor feedback, performance patterns, and corrective actions.
Ideal Profile
* Bachelor\'s, Master\'s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related discipline.
* Minimum 3 years of professional experience in astronomy or astrophysics research, teaching, science communication, academic review, observatory work, or scientific data analysis.
* Strong English communication skills for interpreting detailed guidelines and delivering clear written feedback.
* Thorough understanding of celestial mechanics, stellar evolution, galaxies, cosmology, radiation, and planetary systems.
* Strong knowledge of observational astronomy, spectroscopy, photometry, scientific uncertainty, and physical modeling.
* Ability to identify incorrect assumptions, numerical errors, unsupported conclusions, and misleading scientific explanations.
* Familiarity with astronomical datasets, telescope observations, simulations, or observatory workflows is preferred.
* Experience using Python, Jupyter notebooks, LaTeX, scientific visualization tools, or quantitative research methods is advantageous.
* Ability to review equations, calculations, units, constants, and astrophysical interpretations accurately.
* Understanding of research methodology, evidence quality, measurement limitations, and uncertainty communication.
* Experience leading or supporting researchers, educators, science writers, annotators, reviewers, or QA teams is strongly preferred.
* Excellent attention to scientific terminology, numerical detail, physical plausibility, and documentation.
* Confidence using Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
* Experience developing style guides, calibration tasks, onboarding resources, FAQs, and quality documentation is beneficial.
* Familiarity with AI training, data annotation, large language model evaluation, scientific QA, or rubric-based review is advantageous.
* Availability to complete an AI interview, a domain-specific task, and a recruiter interview.
* Comfortable working independently within a fast-moving remote environment.
Skills Set
* Astronomy quality assurance
* Astrophysics
* Celestial mechanics
* Stellar evolution
* Galactic astronomy
* Cosmology
* Planetary science
* Black hole physics
* Electromagnetic radiation
* Spectroscopy
* Photometry
* Observational astronomy
* Telescope data analysis
* Orbital calculations
* Scientific modeling
* Physical reasoning
* Mathematical verification
* Unit validation
* Scientific uncertainty
* Research methodology
* Astronomical datasets
* Python
* Jupyter notebooks
* LaTeX
* Scientific visualization
* Scientific literature review
* Rubric-based assessment
* AI-generated scientific content evaluation
* Large language model evaluation
* Data annotation quality
* Trainer performance monitoring
* Written scientific feedback
* Style guide development
* Calibration task design
* Contributor onboarding
* Remote team coordination
* Discord
* Google Sheets
* Google Docs
* Quality trackers
* Process improvement
Why Join Us
This opportunity allows astronomy and astrophysics professionals to apply advanced scientific expertise within the expanding artificial intelligence sector. The work directly influences how AI systems explain cosmic phenomena, perform astrophysical calculations, interpret observations, handle scientific uncertainty, and avoid physically impossible or unsupported claims.
Qualified specialists will join a flexible remote expert network and receive early consideration for relevant future assignments. The role also provides exposure to international scientific teams, emerging AI evaluation methods, complex astronomy datasets, and quality frameworks used to improve next-generation language models.
About the Company
YO IT Consulting connects scientists, researchers, and domain specialists with remote AI training and scientific quality projects. Operating from Dubai, United Arab Emirates, the company recruits experts worldwide whose professional knowledge helps improve the scientific accuracy, physical reasoning, evidence awareness, and practical reliability of modern artificial intelligence systems.
