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Atmospheric Modeling Jobs (NOW HIRING)

Xona Space Systems, Inc

Navigation Engineer

Burlingame, CA · On-site

$150K - $180K/yr

Atmospheric Modeling: Develop and validate ionospheric and tropospheric correction models, integrating external data sources as needed. * Integrity Monitoring: Define fault detection and exclusion ...

Leidos

Hyperspectral Image Scientist

Springfield, VA · On-site +1

$92K - $166K/yr

Familiarity with sensor calibration, atmospheric modeling, physics-based exploitation, and sensor phenomenology. * Experience with machine learning or artificial intelligence methods applied to ...

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Atmospheric Modeling information

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$29K

$93.6K

$183K

How much do atmospheric modeling jobs pay per year?

As of Jul 11, 2026, the average yearly pay for atmospheric modeling in the United States is $93,625.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $119,000.00 per year, depending on experience, location, and employer.

What is the difference between Atmospheric Modeling vs Meteorologist?

AspectAtmospheric ModelingMeteorologist
Required CredentialsDegree in atmospheric sciences, meteorology, or related field; often requires programming skillsDegree in meteorology, atmospheric sciences, or related; may include certification or licensing
Work EnvironmentResearch labs, government agencies, or academic institutions; focus on simulations and data analysisWeather stations, media, government agencies; focus on weather forecasting and communication
Industry UsageUsed for climate modeling, weather prediction, and environmental researchUsed for daily weather forecasts, severe weather alerts, and public information

While both roles involve understanding atmospheric phenomena, atmospheric modeling focuses on creating simulations and predictive models using computer algorithms, whereas meteorologists interpret weather data to provide forecasts and public advisories. Both careers require a strong background in atmospheric sciences, but their daily tasks and work environments differ significantly.

What is atmospheric modelling?

Atmospheric modeling is the process used by atmospheric modelers to simulate and analyze the Earth's atmosphere using computer models. It involves applying physics, chemistry, and meteorological data to predict weather patterns, climate changes, and air quality, often utilizing specialized software and data analysis skills. Atmospheric modelers typically work with large datasets and may require knowledge of programming languages like Fortran or Python.

How much do atmosphere models get paid?

Atmospheric modelers typically earn between $60,000 and $110,000 annually, depending on experience, education, and location. Entry-level positions may start around $50,000, while senior roles or those requiring specialized skills can pay over $120,000. Salaries often increase with proficiency in modeling tools and relevant certifications.

Does atmospheric science pay well?

Atmospheric modeling is a specialized field within atmospheric science, and professionals in this area often earn competitive salaries, especially with advanced degrees and experience. Salaries can vary based on location, employer, and level of expertise, with opportunities in government agencies, research institutions, and private companies typically offering higher compensation for skilled analysts familiar with modeling tools and data analysis.

What is an atmosphere model job?

An atmospheric modeling job involves developing and running computer simulations to analyze and predict atmospheric phenomena such as weather, climate, and air quality. These roles typically require skills in programming, data analysis, and knowledge of atmospheric science, often using tools like climate models and modeling software. Professionals in this field may work for research institutions, government agencies, or environmental organizations.

What are the main challenges atmospheric modelers face when integrating new data sources into existing models?

Atmospheric modelers often encounter challenges when incorporating new data sources, such as ensuring data quality, consistency, and compatibility with existing model frameworks. Integrating data from various sensors or satellites may require preprocessing to address differences in resolution, timing, or measurement techniques. Additionally, updating models with new data can impact computational efficiency and require recalibration or validation to maintain accuracy. Close collaboration with data scientists and other researchers is common to streamline this process and ensure robust model performance.

What are the key skills and qualifications needed to thrive as an Atmospheric Modeler, and why are they important?

To thrive as an Atmospheric Modeler, you need a strong background in atmospheric science, mathematics, and computer programming, often supported by an advanced degree in meteorology or a related field. Familiarity with programming languages like Python or Fortran, experience using atmospheric modeling software (such as WRF or GCMs), and proficiency in data analysis tools are typically required. Critical thinking, problem-solving, and effective communication are important soft skills for interpreting model results and collaborating with multidisciplinary teams. These competencies are crucial for producing accurate forecasts, advancing scientific understanding, and informing policy or operational decisions based on atmospheric data.

What is atmospheric modeling?

Atmospheric modeling is the use of computer-based mathematical models to simulate and predict the behavior of the Earth's atmosphere. These models help scientists understand weather patterns, climate change, air pollution, and other atmospheric phenomena. Atmospheric modeling is essential for making weather forecasts, studying long-term climate trends, and assessing environmental impacts. The field combines physics, chemistry, and data analysis to create simulations that can be used by researchers, meteorologists, and policymakers.
More about Atmospheric Modeling jobs
What cities are hiring for Atmospheric Modeling jobs? Cities with the most Atmospheric Modeling job openings:
What are the most commonly searched types of Atmospheric Modeling jobs? The most popular types of Atmospheric Modeling jobs are:
What states have the most Atmospheric Modeling jobs? States with the most job openings for Atmospheric Modeling jobs include:
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Atmospheric Modeling jobs near you
Infographic showing various Atmospheric Modeling job openings in the United States as of July 2026, with employment types broken down into 79% Full Time, 19% Part Time, 1% Temporary, and 1% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $93,625 per year, or $45 per hour.
Research Associate, Atmospheric Science, Machine Learning

Research Associate, Atmospheric Science, Machine Learning

DeVine Consulting, Inc.

Silver Spring, MD • On-site

$90K - $110K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 11 days ago

Job description

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.
If your experience is relevant to the requirements below, and you'd enjoy working in Silver Spring, MD, then please apply!
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.

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