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)