Qualifications Required Education:

Bachelors and five (5) years or more experience; Masters and three (3) years or more experience; PhD and 0 years related experience

Required Qualifications:

A Bachelor's degree in Computer Science, Information Systems, Engineering, Business or other related scientific or technical discipline. Two years of experience in developing and training AI models using large data sets Four years of specialized experience in determining information technology effects on the organizational structure and determining the ability that IT can support/meet organizational goals. With a Master's Degree (in the fields described in Min. Education above): two years experience With a PH.D. (in the fields described in Min. Education above).: no experience required With at least 8 years of specialized experience, a degree is not required. Proficient in Python Programming Experience managing projects with Git Strong interpersonal skills to support collaborative team environments

Desirable Skills:

Basic knowledge of ocean, atmosphere and/or climate and weather processes or a related science. Experience with object storage and traditional disk environments Experience using NetCDF and Zarr datasets Familiarity with High-Performance Computing (HPC) environments and batch queuing systems like Slurm. Experience with modern AI-assisted coding workflows and/or MLOps tools to accelerate development cycles.

Background:

The Allen Institute for Artificial Intelligence (Ai2) and Multiscale Machine Learning In Coupled Earth System Modeling project (M²LInES), in partnership with GFDL, are developing several AI emulators for long time-scale simulations. These include an atmosphere model (ACE), an ocean model (Samudra), and a coupled model emulator (SamudrACE). The Software Engineering for Novel Architectures (SENA) initiative funded GFDL in FY2026 to develop an AI model emulator at seasonal to decadal timescales using data from GFDL's SPEAR mode. The SPEAR emulator project began in January 2026.

Program and Project Details:

The proposed work is a continuation of the previous research of SamudraACE and the SPEAR emulator to apply these methods to the subseasonal to seasonal (S2S) timescales. The work will be done primarily on NOAA systems. When ready, the S2S AI forecast will be transitioned into the

NOAA EAGLE

Project pipeline for operational use.

Target salary range:

$40,001 - $80,000. 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