Research Associate, Atmospheric Science, Machine Learning

DeVine Consulting, Inc.
Silver Spring, MD, United States
about 1 month ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$90,000.0 - $110,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Amazon Web Services Computing Platforms Microsoft Azure Cloud Computing Machine Learning NetCDF Tensorflow Google Cloud Pytorch Deep Learning Information Technology
+1 more
Operational Systems

Job description

  • 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

Requirements

  • 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

Benefits & conditions

Pulled from the full job description

  • 401(k)
  • Health insurance
  • Vision insurance
  • Dental insurance
  • Paid sick time
  • Life insurance
  • Paid holidays, * 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.

About the company

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.

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.indeed.com

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