Lynker is seeking a senior scientific application programmer to support development and operational transition of NOAA’s Warn-on-Forecast Systems (WoFS) under the Precipitation Prediction Grand Challenge (PPGC) program at the National Weather Service (NWS) Office of Modeling and Development (OMD). The successful candidate will develop, integrate, and optimize scientific software and workflows for high performance numerical weather prediction systems to improve forecasts of precipitation and other high impact weather. The candidate will support the operational transition of the cloud-based WoFS Version 1, built on the Weather Research and Forecasting (WRF) Model and the Gridpoint Statistical Interpolation (GSI) data assimilation system. The candidate will also collaborate with the National Severe Storms Laboratory (NSSL) and other partners on the development of the next-generation WoFS (Version 2), based on the Model for Prediction Across Scales (MPAS) and the Joint Effort for Data Assimilation Integration (JEDI), with an emphasis on scientific software development, workflow automation, and high-performance computing.

Duties of the Senior Scientific Application Programmer - Warn-on-Forecast System Developer will include the following:

Successful candidates will support the operational transition of WoFSv1 and the development of WoFSv2 in a cloud computing environment, focusing on scientific software development, workflow automation, system integration, testing, optimization, and operational implementation. Specific responsibilities include:

• Develop, integrate, test, and optimize scientific software to support the operational transition of the cloud-based WoFSv1 system.
• Design and maintain workflows that integrate model preprocessing, data assimilation, forecasting, post-processing, product generation, and visualization.
• Implement, test, and optimize new scientific applications and forecast products for high-impact weather prediction.
• Support the development, integration, and testing of the MPAS-JEDI-based WoFSv2 system.
• Conduct verification, benchmarking, performance evaluation, and retrospective and real-time testing to ensure forecast skill, computational efficiency, and operational readiness.
• Develop and maintain GitHub repositories, software documentation, and version-controlled code to support collaborative scientific software development.

The Ideal Senior Scientific Application Programmer - Warn-on-Forecast System Developer will have the following:

• Education: M.S or higher in Atmospheric Science, Meteorology, Computer Science, Software Engineering, or a closely related field.
• Experience in software development, code management (e.g., GitHub), and integrating complex numerical modeling and data assimilation components.
• Experience in assimilating weather radar, satellite, conventional, mesonet and conventional observations with GSI or JEDI to improve initial conditions for rapid-fresh, convection-allowing ensemble short-range weather prediction systems is preferred.
• Knowledge of Numerical Weather Prediction (NWP) modeling of convective and mesoscale meteorology, ensemble data assimilation, and atmospheric physics and dynamics.
• Experience in developing weather forecasting systems built on WRF and MPAS
• Programming Skills: Strong proficiency in Fortran and modern scripting languages, particularly Python (including scientific packages for AI/ML training and verification). 
• Experience in working within cloud High Performance Computing environments is highly desired.
• Communication: Excellent oral and written communication skills with a proven ability to work both independently and within a multi-disciplinary team.