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Climate Ai Jobs (NOW HIRING)

Published papers in the field of AI in scientific computing, especially in weather & climate applications * Familiarity with common tooling in the Earth-2 ecosystem (xarray, zarr, regridding, weather ...

$175K - $245K/yr

Evaluate emerging risks (cyber, climate, AI) and quantify potential impact. Model reinsurance structures and support enterprise-level risk strategy. Help modernize ERM through automation, data, and ...

AI-led offerings and workflows, vibe coding, prototyping, custom solutions, and a tight feedback ... Job Summary As Manager, Carbon & Climate Advisory, you will lead project delivery across Novata ...

Monthly wellness stipend (mental and physical) If building the relationships and developing bespoke climate strategies to scale climate finance-while using AI as a force multiplier-sound like your ...

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Climate Ai information

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$32.5K

$128.3K

$192K

How much do climate ai jobs pay per year?

As of Jun 9, 2026, the average yearly pay for climate ai in the United States is $128,289.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,500.00 and $158,500.00 per year, depending on experience, location, and employer.

How does a Climate AI specialist typically collaborate with other departments to drive sustainability initiatives?

As a Climate AI specialist, you'll often work closely with cross-functional teams such as sustainability, data science, engineering, and operations. Collaboration is essential to ensure that AI-driven insights translate into actionable strategies for reducing environmental impact. You may participate in regular meetings to align on project goals, share data findings, and coordinate on the implementation of AI solutions. Building strong communication skills and understanding the needs of non-technical departments are key to successfully integrating AI into broader climate and sustainability programs.

What is the difference between Climate Ai vs Climate Analyst?

AspectClimate AiClimate Analyst
Required CredentialsTypically requires a background in data science, machine learning, or environmental science; advanced degrees preferredUsually requires a degree in environmental science, climate studies, or related fields; certifications like GHG accounting can be beneficial
Work EnvironmentPrimarily tech-focused, working with AI models and data platformsOften in research, consulting, or government settings analyzing climate data and reports
Employer & Industry UsageUsed by tech companies, climate-focused startups, and organizations leveraging AI for climate solutionsEmployed by environmental agencies, consulting firms, and research institutions

While Climate Ai focuses on developing AI-driven climate solutions and data modeling, Climate Analysts interpret climate data to inform policy and strategy. Both roles require environmental knowledge, but Climate Ai emphasizes technical AI skills, whereas Climate Analysts focus on data analysis and reporting.

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

To thrive as a Climate AI Specialist, you need a strong background in environmental science, data analytics, and machine learning, often supported by a relevant degree in data science, environmental studies, or computer science. Familiarity with programming languages like Python or R, experience with climate modeling tools, and certifications in AI or data science are typically important. Strong problem-solving skills, interdisciplinary collaboration, and effective communication help translate complex data into actionable climate solutions. These skills are crucial for developing accurate, impactful AI-driven models that address climate challenges and drive informed decision-making.

What is Climate AI and what do professionals in this field do?

Climate AI refers to the application of artificial intelligence technologies to study, predict, and address climate change and its impacts. Professionals working in Climate AI develop machine learning models to analyze climate data, forecast weather patterns, detect environmental risks, and help organizations make data-driven decisions for sustainability. Their work supports governments, researchers, and businesses in mitigating environmental challenges and adapting to changing climate conditions.
More about Climate Ai jobs
What cities are hiring for Climate Ai jobs? Cities with the most Climate Ai job openings:
What states have the most Climate Ai jobs? States with the most job openings for Climate Ai jobs include:
Infographic showing various Climate Ai job openings in the United States as of May 2026, with employment types broken down into 38% Full Time, 56% Part Time, and 6% Contract. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $128,289 per year, or $61.7 per hour.
Senior Scientific Machine Learning Engineer - Earth-2

Senior Scientific Machine Learning Engineer - Earth-2

Nvidia

OR

Full-time

Posted 2 days ago


Job description

NVIDIA's deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world's largest Internet companies. We need passionate and creative people to help us build the AI frameworks underlying the NVIDIA Earth-2 platform: a comprehensive family of open models, libraries, and frameworks that democratize global access to professional-grade weather and climate AI.

What you'll be doing:

  • Work with some of the brightest minds in a premier AI company to develop leading machine learning frameworks, NVIDIA PhysicsNeMo and NVIDIA Earth2Studio, for our academic and industrial partners to build scientific ML technology and workflows for weather, climate, and earth system modeling.

  • Work with internal project teams to validate applications built using the framework on NVIDIA's products, and integrate new functionalities from internal or external projects into the platform

  • Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's Earth-2 technologies, with a focus on weather & climate AI

What we need to see:

  • BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience

  • 5+ yrs of relevant experience

  • Strong Python programming skills

  • Familiarity with containers, numeric libraries, modular software design

  • Deep knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)

  • Experience with development and application of machine learning techniques to solve real world scenarios in weather/climate

  • Experience with scientific visualization. Strong analytical skills with bias for action

  • Good time-management and organization skills to thrive in a fast paced, dynamic environment

  • Solid written and oral communications skills. Good teamwork and interpersonal skills

Ways to stand out from the crowd:

  • Experience using multi-node systems with data-parallel and model-parallel programming, performance optimization. Experience with HPC programming models (OpenMPI, NCCL), and/or CUDA or GPU kernel programming

  • Experience with nonlinear simulation tools and techniques, usage of major simulation codes. Published papers in the field of AI in scientific computing, especially in weather & climate applications

  • Familiarity with common tooling in the Earth-2 ecosystem (xarray, zarr, regridding, weather & climate data stores, etc.)

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and establish teams with the most thoughtful people in the world.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 1, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993