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YO IT Consulting

Astronomer QA Lead - Remote

London
Posted 1 day ago
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Astronomer QA Lead - Remote

Astronomer Quality Assurance Lead

Job Title: Astronomer Quality Assurance Lead

Job Type: Contract (Remote)

About This Role

This hourly, remote contractor role requires an Astronomer Quality Assurance Lead to:

  • Oversee quality, consistency, and trainer performance across astronomy and astrophysics AI training projects.
  • Review AI-generated astronomy/astrophysics content and trainer/QA work, evaluating output quality against project guidelines.
  • Provide precise written feedback ensuring scientific accuracy, mathematical correctness, terminological quality, observational context, clarity, formatting, instruction-following, and project-specific rubric adherence.
  • Identify recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and activate contributors.

Key Focus Areas

  • Scientific accuracy & physical reasoning
  • Mathematical correctness & unit handling
  • Astronomical terminology & clarity
  • Observational context & formatting
  • Training & team alignment

Impact

Your work will directly improve the quality of training data for the world’s largest AI companies and foundation-model labs, ensuring accurate, physically sound, well-documented, and client-aligned astronomy/astrophysics models.

Selection Process

  • AI interview
  • Domain-specific task
  • Recruiter interview Note: No immediate project—opportunities will be offered based on future AI data projects.

Your Profile

  • Education: Bachelor’s, Master’s, or PhD in Astronomy, Astrophysics, Physics, Space Science, Planetary Science, Cosmology, or a closely related field.
  • Language Skills: Strong written and spoken English for clear communication with teams.
  • Experience: 3+ years in astronomy/astrophysics research (or related fields such as teaching, science communication, academic review, data analysis, or observatory work).
  • Domain Expertise: Deep understanding of:
    • Celestial mechanics
    • Stellar evolution
    • Galaxies & cosmology
    • Electromagnetic radiation
    • Observational methods
    • Spectroscopy
    • Planetary systems
    • Black holes
    • Scientific uncertainty
  • Evaluation Skills:
    • Assess content against detailed rubrics, identifying:
      • Incorrect physical assumptions
      • Wrong units or flawed calculations
      • Hallucinated facts
      • Misleading explanations
      • Oversimplified conclusions
  • Tools/Methodologies (Preferred):
    • Python, astronomical datasets
    • Telescope/observatory data
    • Spectroscopy & photometry
    • Simulations, LaTeX, Jupyter notebooks
    • Scientific visualization
  • Team Leadership:
    • Experience leading or supporting remote teams of researchers, educators, reviewers, annotators, science writers, or QAs is highly valued.
  • Technical Proficiency:
    • Comfortable with fast-paced remote workflows using:
      • Discord, Google Sheets/Docs
      • Trackers & dashboards
      • Project management systems
  • Organisational Skills:
    • Highly detail-oriented; ability to maintain:
      • Style guides
      • FAQs & trackers
      • Onboarding & calibration materials
  • Bonus (Preferred):
    • Experience in AI training, data annotation, LLM evaluation, scientific QA, or rubric-based review.

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Key Responsibilities

1. Quality Monitoring & Feedback

  • Spot-check astronomy/astrophysics items, identify recurring issues.
  • Provide ongoing written feedback via direct messages (DMs) and escalate critical/critical issues.
  • Continuous improvement of content & workflows.

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2. Scientific Review

  • Evaluate AI & human-generated astronomy/astrophysics explanations, reasoning, diagrams, observational interpretations, comparisons, and calculations for:
    • Scientific accuracy
    • Logical coherence
    • Practical application

3. Trainer & QA Communication

  • Publish project guideline updates on Discord.
  • Prepare workflow changes, quality expectations, and astronomy-specific review standards.

4. Question Handling

  • Resolve trainer/QA questions promptly, particularly around:
    • Physical assumptions
    • Units & equations
    • Astronomical terminology
    • Observational methods
    • Rubric interpretation

5. Contributor Activation & Management

  • DM inactive contributors, encourage engagement, and track follow-ups.
  • Address availability or performance issues.

6. Documentation

  • Create/maintain:
    • Astronomy-specific style guides
    • Quality trackers
    • FAQs, FAQs, best practices examples
    • Honeypots & calibration tasks
    • Onboarding materials

7. Onboarding & Training

  • Host 1:1 training calls to share:
    • Project expectations
    • Workflows
    • Rubrics
    • Review requirements

8. Quality Alignment & Process Improvement

  • Ensure consistent rubric application across trainers & QAs.
  • Flag high-risk claims (e.g., misleading, overconfident, impossible concepts).
  • Identify recurring quality gaps, propose workflow improvements, and scale QA processes for future projects.
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Skills

Astronomy
Astrophysics
Quality Assurance
Scientific Review
Data Analysis
Communication
Attention to Detail
Python
Scientific Visualization
Project Management
Teaching
Research
Documentation
Team Leadership
AI Training
Mathematics

Location

London, England, United Kingdom

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