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Remote Climate Modeling Jobs (NOW HIRING)

Overstory

Experience with deep learning models for weather or climate data * Experience in remote-first or globally distributed teams Note: We believe that all people are capable of great things. We encourage ...

Carbon Direct

Electrical Engineer

... models for climate technology, grid modernization, and industrial decarbonization teams. Salary ... Remote-friendly work culture with annual company-wide retreats * Reimbursement for your work-from ...

Understory

Underwriter

Madison, WI · On-site +1

For local Madison, WI employees, we offer a hybrid work model. Exceptional remote candidates may be ... Natural catastrophes driven by the volatility of climate change is increasing rates and restricting ...

Understory, Inc.

Underwriter

Madison, WI · Remote

For local Madison, WI employees, we offer a hybrid work model. Exceptional remote candidates may be ... Natural catastrophes driven by the volatility of climate change is increasing rates and restricting ...

McKinstry

BIM Professional

Seattle, WA · On-site +1

$33.58 - $51.83/hr

McKinstry is innovating the waste and climate harm out of the built environment and creating ... Works with peers to further develop modeling and drafting skills while gaining a deeper ...

McKinstry

BIM Professional

Spokane, WA · On-site +1

$33.58 - $46.64/hr

McKinstry is innovating the waste and climate harm out of the built environment and creating ... Works with peers to further develop modeling and drafting skills while gaining a deeper ...

McKinstry

BIM Professional

Portland, OR · On-site +1

$33.58 - $49.24/hr

McKinstry is innovating the waste and climate harm out of the built environment and creating ... Works with peers to further develop modeling and drafting skills while gaining a deeper ...

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How much do remote climate modeling jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for remote climate modeling in the United States is $40.33, according to ZipRecruiter salary data. Most workers in this role earn between $31.25 and $43.51 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Climate Modeler, and why are they important?

To thrive as a Remote Climate Modeler, you need a strong background in atmospheric science, mathematics, and programming, often supported by an advanced degree in a related field. Familiarity with climate modeling software (such as WRF or CESM), statistical analysis tools, and proficiency in programming languages like Python or Fortran are typically required. Strong analytical thinking, problem-solving skills, and clear communication are vital for interpreting complex data and collaborating with multidisciplinary teams. These abilities ensure accurate climate predictions, effective research outcomes, and informed decision-making in environmental policy and planning.

What are some common challenges faced when collaborating remotely as a climate modeler, and how can they be addressed?

Remote climate modelers often work with interdisciplinary teams spread across different time zones, which can make real-time communication and data sharing challenging. To overcome these obstacles, it's important to establish clear communication channels and regular virtual meetings to align on project goals and timelines. Leveraging collaborative tools for code versioning, data management, and documentation also helps ensure smooth teamwork. Staying proactive about updates and maintaining open lines of feedback can significantly improve coordination and project outcomes.

What is remote climate modeling?

Remote climate modeling refers to the use of computer simulations and data analysis to study and predict climate patterns, typically from a remote location rather than a traditional office or laboratory. Professionals in this field use various climate models to understand atmospheric, oceanic, and land processes and assess future climate scenarios. This work often involves collaborating with scientists, analyzing large datasets, and using advanced software tools. Remote positions allow climate modelers to contribute to important environmental research while working from anywhere with a reliable internet connection.
More about Remote Climate Modeling jobs
What cities are hiring for Remote Climate Modeling jobs? Cities with the most Remote Climate Modeling job openings:
What are the most commonly searched types of Climate Modeling jobs? The most popular types of Climate Modeling jobs are:
What states have the most Remote Climate Modeling jobs? States with the most job openings for Remote Climate Modeling jobs include:
What job categories do people searching Remote Climate Modeling jobs look for? The top searched job categories for Remote Climate Modeling jobs are:
Remote Climate Modeling jobs near you
Infographic showing various Remote Climate Modeling job openings in the United States as of July 2026, with employment types broken down into 50% Internship, and 50% Full Time. Highlights an 100% Remote job distribution, with an average salary of $83,896 per year, or $40.3 per hour.

Staff Machine Learning Engineer - Wildfire

Overstory

On-site, Remote

Other

Posted 6 days ago

Job description

Role & Team

As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation structure, fuel loads, and wildfire risk from satellite and environmental data. You'll help shape the next generation of Overstory's modeling capabilities by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain expertise.

Reporting to our VP of Product Engineering, you'll work closely with data scientists, ML engineers, and product teams to ensure our wildfire models are accurate, robust, and production-ready - balancing scientific rigor with practical engineering excellence. As a senior technical leader, you'll mentor other engineers, drive architectural decisions, and define standards for modeling, experimentation, and deployment across Overstory.

Time zone requirement: Eastern North America (NST, AST, EST)

What You'll Do

In collaboration with data, ML, and science colleagues, you will:

  • Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies.
  • Design and maintain robust data and feature pipelines for large-scale geospatial and temporal data.
  • Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to real-world impact.
  • Build reproducible experimentation frameworks and model evaluation workflows.
  • Scale models from research to production with a focus on performance, reliability, and explainability.
  • Lead the evolution of ML systems, tooling, and processes - ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable.
  • Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments.
Skills & Experience
  • Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by the opportunity to reduce wildfire risk through data-driven insights
  • 10+ years of experience designing and building production-grade ML pipelines and systems 
  • Strong background in deep learning, computer vision, or remote sensing
  • Skilled in designing end-to-end ML systems - from data ingestion and preprocessing to deployment and monitoring
  • Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, Spark, or GeoPandas
  • Familiarity with GCP and Vertex AI, or similar cloud-based ML platforms
  • Strong communication skills and ability to collaborate across technical and scientific domains
  • Comfortable leading architectural discussions and mentoring other engineers
Nice To Have
  • Background in wildfire science, forestry, or remote sensing
  • Experience integrating physics-based models with ML or working with active learning and uncertainty quantification
  • Experience in model interpretability and data provenance for environmental ML systems
  • Experience with deep learning models for weather or climate data
  • Experience in remote-first or globally distributed teams

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer
  • Competitive, location-specific compensation and benefits 
  • Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
  • Home office stipend, coworking and ongoing education budgets 
  • A company culture that genuinely embodies each of our core values
  • To be part of truly mission-driven work that reduces wildfires, protects earth's natural resources and helps solve our climate crisis

Apply