Jobs Companies micro1 STEM Expert

Sobre esta vaga de STEM Expert na micro1

micro1 · Remoto · Remote — 58 countries

Hardware Expert

Pay: $50–$100/hour

Location: Global, fully remote

Job Type: Contractor (~15 hours per week)

Schedule: Flexible—you choose the hours and days you work, including weekends if desired


We are looking for highly skilled STEM and scientific-domain experts to contribute to an AI training project involving technical problem-solving, scientific reasoning, data analysis, and Python.


The work involves solving, reviewing, and validating challenging problems within your area of expertise. A representative task may require analyzing a scientific or mathematical problem, developing a rigorous solution, using Python to perform calculations or simulations, and evaluating whether an AI-generated answer is technically correct.


Candidates are not expected to be experts across every STEM discipline. We are looking for deep expertise in at least one of the following areas:

  1. Chemistry
  2. Biology
  3. Mathematics
  4. Physics
  5. Earth Science / Geoscience / Environmental Science
  6. Linguistics / Computational Linguistics
  7. Robotics


Adjacent scientific or quantitative disciplines may also be considered where the candidate's expertise is directly relevant.


What You’ll Work On


  1. Solve complex scientific, mathematical, or technical problems within your domain of expertise.
  2. Review AI-generated solutions for factual, mathematical, and scientific correctness.
  3. Identify incorrect assumptions, reasoning errors, missing constraints, and subtle technical mistakes.
  4. Develop clear and reproducible reference solutions.
  5. Use Python for scientific computation, data analysis, simulations, or solution validation.
  6. Interpret equations, experimental results, datasets, technical diagrams, or scientific literature where relevant.
  7. Perform sanity checks and validate numerical or analytical results.
  8. Compare alternative solution approaches and determine whether conclusions are supported by the evidence.
  9. Clearly explain technical reasoning and corrections.


Required Qualifications

  1. Strong expertise in at least one relevant STEM or scientific domain.
  2. Practical proficiency with Python.
  3. Strong scientific, mathematical, or quantitative problem-solving ability.
  4. Ability to reason carefully about assumptions, constraints, edge cases, and sources of error.
  5. Ability to explain complex technical concepts and solutions clearly.
  6. Experience validating, reviewing, or troubleshooting technical work.


Relevant Python tools may include NumPy, SciPy, pandas, SymPy, Jupyter, or domain-specific scientific libraries. No particular Python library is mandatory.


Expertise may come from academic research, industry, teaching, engineering, independent technical work, or other demonstrated experience. A specific degree or number of years of experience is not strictly required if you can demonstrate strong expertise in your field.


Process

  1. Apply to the role and complete the screening questions.
  2. Complete an AI interview of approximately 30 minutes.
  3. Complete the hiring manager review.


Compensation Structure


Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow.

Minimum submission requirements apply.


Start Timeline & Availability

We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

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Sobre a micro1

micro1 is a human data and talent infrastructure company focused on improving AI systems through high-quality expert input.


It connects vetted domain specialists with AI teams and enterprises to produce training data, run model evaluations, and improve reasoning performance in advanced AI systems.


The platform combines a talent marketplace with AI-driven screening and matching tools, enabling faster access to specialized contributors for tasks like LLM training, agent evaluation, and structured data creation.

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