Scientific AI Programmer

SAIC • Princeton, NJ

6d • Onsite

About The Position

SAIC is seeking an experienced Scientific AI programmer for a position at NOAA’s Geophysical Fluid Dynamics Laboratory (GFDL) that will focus on creating a complex earth system model emulator. Through the work of this position, SAIC will develop a seasonal to subseason (S2S) AI weather forecast model. The Scientific AI programmer will evaluate an existing emulator and develop a prototype for the S2S timescale. You will work collaboratively with federal, contractor, university, and private sector scientists and developers and with the scientific evaluation team to assess the readiness of the AI forecast model for operational use. This position requires an ability to obtain and maintain a Public Trust background investigation. This position is located in Princeton, NJ.

Requirements

• 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

Nice To Haves

• 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.

Responsibilities

• Evaluate the existing seasonal to decadal AI emulator prototype to determine its utility for S2S timescales
• Build an S2S AI emulator using SPEAR hindcasts, reanalysis, and other earth-system data for S2S forecasts
• Determine the operational readiness of the S2S AI emulator
• Coordinate with federal, contractor, university, and private sector scientists to align variables and training frameworks with research objectives
• Deliver status updates through various communication channels such as team meetings and written reports

What This Job Offers

• Job Type: Full-time
• Career Level: Senior