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Astronomer Quality Assurance Lead (QAL)

SME Careers Remote

Education

Any

Type

hourly

Pay Rate

$110/task

Listed

21d ago

ℹ️ Job Reference ID

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AstroandSpaceQAL-26-135

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SME Careers: our referral track record

We've referred 1267 candidates to SME Careers roles. 15% (188) were placed.

SME Careers: typical time to hire

Based on 188 tracked placements across all SME Careers roles on our site.

23 days 54 days (median) 108 days
Within 2 weeks
12%
Within 6 weeks
48%
Within 13 weeks
72%

About this Role

From the SME Careers listing

In this hourly, remote contractor role, you will work as an Astronomy / Astrophysics Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across astronomy and astrophysics AI training projects. You will review AI-generated astronomy/astrophysics content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.

You will assess work for scientific accuracy, physical reasoning, mathematical correctness, terminology quality, unit handling, observational context, clarity, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong astronomy/astrophysics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote expert teams.

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. Your astronomy/astrophysics quality leadership will directly help improve the world’s premier AI models by ensuring that astronomy and astrophysics training data is accurate, physically sound, clearly explained, well-documented, and aligned with client expectations.

Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter.

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.

Key responsibilities

  • Quality monitoring: Spot-check astronomy/astrophysics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
  • Scientific review: Evaluate AI-generated astronomy/astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning for accuracy and clarity.
  • Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and astronomy/astrophysics-specific review standards.
  • Question handling: Respond to trainer/QA questions clearly and promptly, especially around physical assumptions, units, astronomical terminology, observational methods, formulas, and rubric interpretation.
  • Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed.
  • Documentation: Create and maintain astronomy/astrophysics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
  • Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and astronomy/astrophysics-specific review requirements.
  • Quality alignment: Ensure all trainers and QAs apply astronomy/astrophysics review guidelines consistently and understand updates as projects evolve.
  • Risk review: Flag misleading, overconfident, physically impossible, numerically incorrect, or poorly sourced astronomy/astrophysics claims.
  • Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for astronomy/astrophysics AI training projects.

Your profile

  • Bachelor’s, Master’s, or PhD degree in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field.
  • Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear written feedback.
  • 3+ years of experience in astronomy/astrophysics research, teaching, science communication, academic review, data analysis, observatory work, or related scientific workflows.
  • Strong understanding of celestial mechanics, stellar evolution, galaxies, cosmology, electromagnetic radiation, observational methods, spectroscopy, planetary systems, black holes, and scientific uncertainty.
  • Ability to evaluate astronomy/astrophysics content against detailed rubrics and identify issues such as incorrect physical assumptions, wrong units, flawed calculations, hallucinated facts, misleading explanations, or oversimplified conclusions.
  • Familiarity with tools or methods such as Python, astronomical datasets, telescope/observatory data, spectroscopy, photometry, simulations, LaTeX, Jupyter notebooks, or scientific visualization is preferred.
  • Experience leading or supporting remote teams of researchers, educators, reviewers, annotators, science writers, or QAs is strongly preferred.
  • Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
  • Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, calibration tasks, and documentation.
  • Experience with AI training, data annotation, LLM evaluation, scientific QA, academic review, or rubric-based review is a strong plus.

🌍 Geographic Availability This role is available to qualified experts globally. However, as a U.S.-based company, SME Careers complies with U.S. export control and sanctions regulations. Eligibility depends on your country of residence and any applicable trade restrictions. Some projects may have additional language or region-specific requirements.

💰 Pay Rate May Vary Based on Your Location Your actual compensation will be determined based on your location and local market conditions. See regional job listings for localized pay information, or the application process will clarify your specific rate.

If you're unsure whether you're eligible, proceed with the application—SME's screening will determine your jurisdiction status and applicable compensation.

Requirements

  • Trainer Feedback
  • Cosmology
  • Physics Review
  • Astronomy
  • Scientific Reasoning
  • LLM evaluation
  • Observational Astronomy

Key Responsibilities

  • Quality monitoring: Spot-check astronomy/astrophysics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
  • Scientific review: Evaluate AI-generated astronomy/astrophysics explanations, calculations, diagrams, observational interpretations, comparisons, and step-by-step reasoning for accuracy and clarity.
  • Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and astronomy/astrophysics-specific review standards.
  • Question handling: Respond to trainer/QA questions clearly and promptly, especially around physical assumptions, units, astronomical terminology, observational methods, formulas, and rubric interpretation.

Why This Role

Most AI training platforms cap you at task-taker. SME Careers is different: a Astronomer Quality Assurance Lead (QAL) who performs well gets promoted, not just re-queued. It's a genuine path from freelance STEM work into a leadership track, with weekly Deel payouts and flexible hours along the way.

Skills & Categories

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Frequently Asked Questions

Does SME Careers offer a path for advancement?

Yes. SME Careers is unusual among AI training platforms for this: it publishes an explicit career ladder, Data Trainer, then Quality Analyst, then QA Lead, then Project Manager. Consistent, high-quality work is what moves you up it.

How does SME Careers pay freelancers?

Weekly, through Deel. Deel also handles tax compliance, which is how SME Careers pays contractors across more than 40 countries without running its own international payroll.

Is SME Careers work ongoing or project-based?

Project-based. Assignment duration and availability vary by project, but consistently high-quality work earns priority access to whatever comes next.

Is AI training work the same as traditional consulting?

No. Instead of client deliverables, you're given complex scenarios to evaluate: grading the AI's logic, correcting its hallucinations, and supplying expert-level reasoning it doesn't have on its own. The job is closer to teaching than consulting.

Why do these AI training roles pay so much?

Because general knowledge isn't what's being tested. The model already knows the basics; what it needs is expertise on edge cases, the rare, difficult, highly technical judgment calls only a senior professional in the field would make correctly.

What does the day-to-day workload look like for elite-expert AI training roles?

Slow and deep, not fast and repetitive. A single task can take 45-60 minutes of researching citations or verifying complex calculations. Quality is what's being measured here, not throughput.

What does STEM work look like for a Astronomer Quality Assurance Lead (QAL)?

Tasks here are scoped to STEM, not generic labeling. As a Astronomer Quality Assurance Lead (QAL), expect to draw on real domain judgment (evaluating outputs, correcting errors, or providing expert reasoning specific to STEM) rather than following a one-size-fits-all rubric. If you don't have hands-on STEM background, this is likely not the right listing to start with.

What happens when I click Apply on this listing?

You'll be taken to SME Careers's external site to complete your application there. This listing links through a referral, but the process is identical to applying directly; the link just routes you correctly. Create an account on their site and follow their onboarding steps.

Who is behind SME Careers?

SME Careers is the expert talent division of SuperAnnotate, an AI data infrastructure platform, connecting domain experts with high-level AI training projects.