Atmospheric Science Expert (Masters/PhDs)
Alignerr · United States
- Hybrid
- Contract
- $50,000 / year
- United States
Job highlights
- Develop AI training data in atmospheric science.
- Apply climate modeling and ecology expertise.
- Evaluate AI scientific reasoning accuracy.
- Work remotely with flexible hours.
- Contribute to impactful AI research projects.
About the role
Atmospheric Science Expert (AI Training)
What if your deep expertise in atmospheric science could directly shape how AI understands our planet's most complex systems — from climate modeling to ecological dynamics? We're looking for Atmospheric Science experts to develop and evaluate advanced scientific problems that train the next generation of AI models to reason with genuine scientific rigor.
This is a fully remote, flexible contract role built for researchers and domain specialists. No AI background needed — just a command of atmospheric science and a passion for applying your knowledge to problems that matter.
About the Role
- Organization: Alignerr
- Type: Hourly Contract
- Location: Remote
- Commitment: 10–40 hours/week
What You'll Do
- Develop, solve, and review advanced atmospheric and environmental science problems with real-world relevance
- Apply your expertise in climate modeling, ecology, sustainability, or related disciplines to craft complex, high-quality problem statements
- Evaluate AI-generated scientific reasoning for accuracy, depth, and methodological soundness
- Collaborate asynchronously with AI researchers and fellow domain experts to push the boundaries of AI scientific reasoning
- Ensure scientific rigor, clarity, and intellectual depth across all deliverables
- Work independently on task-based assignments — fully on your own schedule
Who You Are
- Master's or PhD in Atmospheric Science, Environmental Science, or a closely related field
- Strong expertise in at least one of: climate modeling, ecology, atmospheric dynamics, or sustainability science
- Proficient in Python or R for research or data analysis
- Exceptional written communicator — able to express complex ideas with precision and clarity
- Detail-oriented and intellectually rigorous in your approach to scientific problems
- Self-motivated and comfortable working independently in an asynchronous environment
Nice to Have
- Prior experience with data annotation, data quality evaluation, or AI training workflows
- Background in scientific writing, peer review, or academic publishing
- Familiarity with AI tools or language model evaluation as an end user
- Experience mentoring students or communicating science to non-specialist audiences
Why Join Us
- Work on cutting-edge AI projects alongside leading research labs and AI teams
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, intellectually stimulating work
- Apply your scientific expertise to problems with real-world impact at a global scale
- Potential for ongoing work and contract extension as new projects launch
Key skills/competency
- Atmospheric Science
- AI Training
- Climate Modeling
- Ecology
- Sustainability Science
- Python
- R
- Scientific Writing
- Data Analysis
- Research
Skills & topics
- Atmospheric Science
- AI Training
- Climate Modeling
- Ecology
- Sustainability
- Python
- R
- Data Analysis
- Scientific Research
- Remote Work
How to get hired
- Tailor your resume: Highlight your Master's/PhD in Atmospheric Science and relevant research experience.
- Showcase technical skills: Emphasize Python/R proficiency and any AI/data annotation background.
- Demonstrate communication: Provide examples of explaining complex scientific ideas clearly.
- Highlight independence: Stress your ability to work autonomously in remote settings.
- Apply early: Submit your application promptly for this remote contract role.
Technical preparation
Master Python/R for data analysis.,Practice formulating complex scientific problems.,Review AI model outputs for accuracy.,Familiarize with AI evaluation workflows.
Behavioral questions
Describe a complex scientific problem you solved.,How do you ensure clarity in technical writing?,How do you manage your time independently?,Give an example of rigorous scientific evaluation.
Frequently asked questions
- What is the work arrangement for the Atmospheric Science Expert role at Alignerr?
- The Atmospheric Science Expert role at Alignerr is a fully remote, flexible hourly contract position. This means you can work from anywhere and choose your own hours within the 10-40 hours/week commitment.
- Do I need prior AI experience to apply for the Atmospheric Science Expert job at Alignerr?
- No, prior AI experience is not required for the Atmospheric Science Expert role at Alignerr. The focus is on your deep expertise in atmospheric science, and you'll be trained on how to apply it to AI models.
- What specific areas of atmospheric science are most relevant for this role at Alignerr?
- Alignerr is particularly interested in expertise within climate modeling, ecology, atmospheric dynamics, or sustainability science. However, any closely related field within atmospheric or environmental science will be considered.
- What is the expected commitment for the Atmospheric Science Expert role?
- The commitment for this role is flexible, ranging from 10 to 40 hours per week, making it suitable for individuals seeking part-time or more intensive contract work.
- How does Alignerr ensure the quality of AI training data for atmospheric science?
- Alignerr relies on domain experts like Atmospheric Science PhDs and Masters holders to develop, solve, and review advanced scientific problems. Your role will involve evaluating AI-generated reasoning for accuracy and methodological soundness.
- What kind of collaboration is expected in this remote role at Alignerr?
- Collaboration for the Atmospheric Science Expert role is primarily asynchronous. You will work independently but have opportunities to collaborate with AI researchers and fellow domain experts.
- What are the key deliverables for an Atmospheric Science Expert at Alignerr?
- Key deliverables include developing and solving complex scientific problem statements, evaluating AI reasoning, and ensuring the scientific rigor and clarity of all contributed materials.