Meteorologists – Weather Model Labeling

Mercor

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profile Job Location:

London - UK

profile Monthly Salary: Not Disclosed
Posted on: 10 hours ago
Vacancies: 1 Vacancy

Job Summary

Mercor is hiring experienced meteorologists to help train a large-scale physics AI model by interpreting High-Resolution Rapid Refresh (HRRR) outputs. You will analyze single-frame HRRR model visualizations (4 images per timestamp) and produce high-quality natural-language labels that clearly explain:

  • What weather phenomena are present and

  • Why they are occurring based strictly on the model data.

This is a high-judgment expert role for meteorologists comfortable diagnosing synoptic and mesoscale features directly from model fields.

What Youll Do

  • Interpret HRRR outputs at a specific time step

  • Identify key atmospheric features (e.g. troughs jet streaks fronts instability convection)

  • Explain the physical mechanisms driving observed conditions (e.g. vorticity advection lift moisture transport upper-level divergence)

  • Produce clear structured technically accurate written explanations

All labels must be grounded strictly in HRRR data (no radar/satellite/AFD references).

Requirements

  • Degree in Meteorology / Atmospheric Science OR 2 years of operational forecasting experience

  • Strong synoptic and mesoscale analysis skills

  • Deep understanding of atmospheric dynamics and thermodynamics

  • Clear precise technical writing ability

Evaluation Process

  • Behavioral interview (forecast reasoning & decision-making)

  • Short technical assessment (500 mb chart interpretation)

Mercor is hiring experienced meteorologists to help train a large-scale physics AI model by interpreting High-Resolution Rapid Refresh (HRRR) outputs. You will analyze single-frame HRRR model visualizations (4 images per timestamp) and produce high-quality natural-language labels that clearly explai...
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Key Skills

  • Python
  • C/C++
  • Fortran
  • R
  • Data Mining
  • Matlab
  • Data Modeling
  • Laboratory Techniques
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  • SAS
  • Systems Analysis
  • Dancing