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Atmospheric Modeling Jobs in California (NOW HIRING)

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Atmospheric Modeling information

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$28.4K

$91.7K

$179.2K

How much do atmospheric modeling jobs pay per year?

As of Aug 23, 2026, the average yearly pay for atmospheric modeling in California is $91,680.00, according to ZipRecruiter salary data. Most workers in this role earn between $61,201.00 and $116,528.00 per year, depending on experience, location, and employer.

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.

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 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 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.

Do atmospheric modeling scientists make good money?

Atmospheric modeling scientists typically earn competitive salaries that vary based on experience, education, and location. Entry-level positions may start around $60,000 annually, while experienced professionals can earn over $100,000, especially with advanced skills in programming and data analysis. The field often requires a strong background in atmospheric sciences, computer modeling, and relevant certifications.

What are the most commonly searched types of Atmospheric Modeling jobs in California?

The most popular types of Atmospheric Modeling jobs in California are:

What are popular job titles related to Atmospheric Modeling jobs in California?

For Atmospheric Modeling jobs in California, the most frequently searched job titles are:

What job categories do people searching Atmospheric Modeling jobs in California look for?

The top searched job categories for Atmospheric Modeling jobs in California are:

What cities in California are hiring for Atmospheric Modeling jobs?

Cities in California with the most Atmospheric Modeling job openings:

Atmospheric Modeling jobs near you
Infographic showing various Atmospheric Modeling job openings in California as of August 2026, with employment types broken down into 38% Full Time, 58% Part Time, and 4% Temporary. Highlights an 96% In-person, and 4% Remote job distribution, with an average salary of $91,680 per year, or $44.1 per hour.

Senior AI/ML Scientist, Planetary Science

Relativity Space

Long Beach, CA • On-site

$99K - $136K/yr

Full-time

Re-posted 3 days ago

Relativity Space rating

9.7

Company rating: 9.7 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

2nd of 72 rated aerospace companies

Job description

Job Summary:
Relativity Space is building rockets to serve today’s needs and tomorrow’s breakthroughs. They are seeking a Senior AI/ML Scientist to develop and deploy machine learning systems for their 2028 Mars orbital mission, focusing on enhancing atmospheric modeling and multi-modal data fusion.
Responsibilities:
• Develop and deploy machine learning systems that unlock new science from our 2028 Mars orbital mission.
• Enhance Mars atmospheric modeling and do weather forecasting.
• Develop and apply Machine Learning techniques to combine Earth-derived atmospheric datasets and known Martian atmospheric physics to create a weather forecasting model.
• Develop and build methods that reconstruct coherent 3D representations by integrating complementary datasets of 2D surface images, 3D surface models, geologic mapping of units, and radar depth soundings.
• Build systems that monitor observations, analyze them in real-time on the spacecraft and detect scientifically significant events based on known phenomenology of Mars as well as novelty detection.
• Develop the AI decision-making layer that closes the loop, autonomously re-tasking the spacecraft to acquire follow-up observations from onboard inference on flight hardware.
• Drive your own problem framing, build and evaluate systems end-to-end, and communicate results clearly to scientists and engineers alike.
Qualifications:
Required:
• PhD in machine learning, computer science, physics, or a related technical field, and 3+ years of relevant industry experience
• Demonstrated experience with transfer learning, domain adaptation or model fine-tuning, particularly in low-data or out-of-distribution settings
• Experience with applying machine learning in physical datasets
• Working knowledge of multi-modal data fusion
• Ability to own problems end-to-end: from dataset understanding through model development, evaluation, and deployment
• Excited to collaborate with a diverse group of scientists and engineers, and further planetary science
Company:
Relativity Space is an aerospace company that designs, develops, and builds 3D printed rockets. Founded in 2015, the company is headquartered in Long Beach, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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