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Climate Research Scientist Machine Learning Jobs in San Ramon, CA

Substrate

Research Scientist, AI

San Francisco, CA · On-site

$150K - $275K/yr

Research Scientist, AI Substrate is addressing one of the most important technological problems ... Integrate machine learning techniques to accelerate scientific simulations, modeling, and ...

Lead Allies Inc.

Research Scientist

San Francisco, CA · On-site

Research Scientist / Machine Learning Scientist Location: SF Bay Area/Hybrid / Remote Type: Full-Time About the Role: The Client is seeking a variety of Machine Learning Scientist to help advance how ...

Skild AI

Research Scientist

San Mateo, CA

Position Overview We are looking for Research Scientists to lead the effort in developing the next ... We are looking for people with proven expertise in machine learning and/or robotics, who are ...

OpenAI

Research Scientist

San Francisco, CA · On-site

As a Research Scientist, you will develop innovative machine learning techniques and advance the research agenda while collaborating with peers across the organization. Responsibilities : • Have a ...

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All JobsClimate Research Scientist Machine Learning JobsClimate Research Scientist Machine Learning Jobs in San Ramon, CA

Climate Research Scientist Machine Learning information

See San Ramon, CA salary details

$56.4K

$145.4K

$194.4K

How much do climate research scientist machine learning jobs pay per year?

As of Jul 29, 2026, the average yearly pay for climate research scientist machine learning in San Ramon, CA is $145,408.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,100.00 and $193,300.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Climate Research Scientist specializing in Machine Learning, and why are they important?

To thrive as a Climate Research Scientist specializing in Machine Learning, you need a solid background in climate science, statistical analysis, and advanced machine learning techniques, typically supported by a graduate degree in a related field. Experience with programming languages like Python or R, familiarity with climate modeling software, and proficiency in machine learning frameworks such as TensorFlow or PyTorch are highly valuable. Strong analytical thinking, problem-solving abilities, and effective communication skills help you explain complex findings to diverse audiences and collaborate across disciplines. These skills and qualities are crucial for advancing climate research, developing innovative solutions, and informing policy decisions based on robust data analysis.

What does a Climate Research Scientist specializing in Machine Learning do?

A Climate Research Scientist who specializes in Machine Learning uses advanced algorithms and computational models to analyze climate data and improve predictions about climate change. They work with large datasets from satellites, weather stations, and simulations to identify patterns, make forecasts, and assess environmental impacts. Their work helps inform policy decisions, guide mitigation strategies, and advance our scientific understanding of the Earth's climate system. Collaboration with other scientists, governments, and organizations is often a key part of the role.

How do Climate Research Scientists specializing in Machine Learning typically collaborate with multidisciplinary teams?

Climate Research Scientists with expertise in Machine Learning often work closely with meteorologists, data engineers, environmental scientists, and policy experts. They contribute by developing and refining predictive models using large climate datasets, while also translating complex outputs into actionable insights for decision-makers. Collaboration often involves regular team meetings, joint publications, and integrating domain expertise to ensure that the models are both scientifically robust and practically useful. Strong communication skills are valuable, as these scientists frequently explain technical concepts to colleagues from non-technical backgrounds.

What is the difference between Climate Research Scientist Machine Learning vs Climate Data Analyst?

AspectClimate Research Scientist Machine LearningClimate Data Analyst
Required CredentialsMaster's or PhD in Climate Science, Data Science, or related fields; knowledge of machine learningBachelor's or Master's in Environmental Science, Data Analysis, or related fields; proficiency in data tools
Work EnvironmentResearch labs, universities, environmental agencies, often collaborative and interdisciplinaryGovernment agencies, consulting firms, NGOs; focus on data processing and reporting
Employer & Industry UsageResearch institutions, academia, environmental organizations integrating machine learningPolicy organizations, environmental consultancies analyzing climate data

While both roles involve climate data, Climate Research Scientist Machine Learning focuses on developing predictive models using advanced algorithms, whereas Climate Data Analysts primarily process and interpret climate datasets to inform decisions. The former requires more specialized knowledge in machine learning techniques, while the latter emphasizes data management and reporting skills.

What are popular job titles related to Climate Research Scientist Machine Learning jobs in San Ramon, CA? For Climate Research Scientist Machine Learning jobs in San Ramon, CA, the most frequently searched job titles are:
What job categories do people searching Climate Research Scientist Machine Learning jobs in San Ramon, CA look for? The top searched job categories for Climate Research Scientist Machine Learning jobs in San Ramon, CA are:
What cities near San Ramon, CA are hiring for Climate Research Scientist Machine Learning jobs? Cities near San Ramon, CA with the most Climate Research Scientist Machine Learning job openings:
Climate Research Scientist Machine Learning jobs near you
Infographic showing various Climate Research Scientist Machine Learning job openings in San Ramon, CA as of July 2026, with employment types broken down into 9% Internship, 72% Full Time, 9% Part Time, 5% Temporary, and 5% Contract. Highlights an 91% In-person, and 9% Remote job distribution, with an average salary of $145,408 per year, or $69.9 per hour.

Machine Learning Research Scientist

Autoscience

Menlo Park, CA • On-site

Full-time

PTO

Re-posted 18 days ago

Job description

Company Description

At Autoscience Institute, we create AI systems that autonomously conduct AI research. Recently, we announced the first AI agent to autonomously create peer-reviewed literature (ICLR 2025 Workshops). We are passionate about pushing the boundaries of artificial intelligence and contributing to groundbreaking advancements in the field.

Role Description

This is a full-time on-site role for a Machine Learning Research Scientist located in the San Francisco Bay Area.

  • Work directly with the founder to develop autonomous research systems that ideate, experiment, and improve customer models.

  • Collaborate with the engineering team to build and deploy production-ready research systems.

  • RL post-train and fine-tune reasoning models to automate components of the machine learning research process.

  • Stay current with the latest developments in AI research and automation.

Qualifications:

  • Education: PhD or equivalent research experience in Computer Science, Machine Learning, Artificial Intelligence, or a related field. Exceptional candidates with strong research contributions are encouraged to apply regardless of formal degree.

  • Research: Publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, etc) or equivalent industry experience at corporate AI research labs (Microsoft, Google, Nvidia, TRI etc).

  • Technical: Expertise in training machine learning models, including deep learning, reinforcement learning or genetic algorithms. This does not include building multi-agent systems using LLM APIs or building RAG-based agents.

  • Curiosity: Passion for accelerating scientific discovery through AI and willingness to explore uncharted directions with minimal supervision.

Recommended Qualifications

  • Systems: Experience building scalable and production-ready machine learning pipelines or large-scale model training (distributed model training over >64 GPUs).

  • Science: Any background or proven interested in Automated Scientific Research is a plus.

Benefits & Perks

  • Our comp is competitive against major LLM frontier lab packages

  • Unlimited PTO and flexible working arrangements

  • Conference attendance and publication support

Our Culture

We're a team of passionate researchers and engineers working to automate scientific discovery. We believe in the power of AI to accelerate scientific discovery and are committed to responsible AI development
We are an e-verify employer.