Research Associate, Atmospheric Science, Machine Learning

DeVine provides technical and scientific support to government clients in Oceanography & Atmospheric Science among other technical disciplines. Our company is looking for a Research Associate , with experience in Atmospheric Science and Machine Learning (ML), to join DeVine in a full time capacity. This position will be supporting a government customer, hence only US Citizens may be considered for hire. Candidates who meet/exceed every requirement may be considered for remote work. DeVine contributes to projects in data modeling, remote sensing & machine learning. We collaborate with our clients in scientific analysis of the Earth’s atmosphere & ocean and land surfaces, as well as astronomy and astrometry. We help our clients test and operate space-based, air-based, subsurface, and land and ocean surface-based sensors. The successful hire will contribute to improvements in weather forecast performance to deliver more accurate weather insights to our customers. Duties: Conduct innovative research at the intersection of weather prediction and machine learning, including approaches that leverage observations from satellite constellation Develop, verify, and document forecast improvements that provide measurable value to customers Partner with engineering and product teams to transition research advances into scalable, operational systems Communicate results through internal reviews, customer discussions, and, where appropriate, conferences or publications Contribute broadly to improving forecasts and overall product performance Required experience and credentials: Graduate degree in atmospheric science, meteorology, computer science, or a related field 2+ years of experience developing ML models for weather applications Strong ML engineering fundamentals, including model training, validation, evaluation, and documentation Training, running, and verifying AI-based weather prediction models Working in cloud-based computing environments Handling large meteorological datasets and common data formats at scale Modern deep learning frameworks (e.g., PyTorch or TensorFlow) Large geophysical dataset formats (GRIB, NetCDF, ZARR) Proficiency with deep learning frameworks (e.g., PyTorch, TensorFlow) Familiarity with cloud-based computing environments (AWS, GCP, Azure) Strong written and verbal communication skills Ability to manage multiple projects and balance competing priorities About the position: Position Type: Full-time, Must be U.S. Citizen Location: Silver Spring, MD Benefits: Medical, Dental, Vision, 401K, Life Insurance, Paid Holidays, Paid Sick Leave and Paid Vacation Compensation: $90K to $110K per year salary range DOE and skills Equal Opportunity Employer We are committed to a policy of assuring that all applicants for employment are recruited, hired and assigned on the basis of qualifications and merit without discrimination based on any protected classification, including, but not limited to, race, color, religion, sex, sexual orientation, national origin, veteran status, age, disability, handicap, marital status, or any other characteristic protected by applicable laws. #J-18808-Ljbffr National Science Teachers Association