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Climate Research Scientist Machine Learning Jobs in San Ramon, CA

Voiceflow

Machine Learning Research Scientist

San Mateo, CA · On-site

$100 - $150/hr

  • PTO

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 ...

New

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 ...

Perdurable AI

AI Research Scientist

San Francisco, CA · On-site

$120 - $160/hr

PhD or MS in Computer Science, Machine Learning, or related field * 3+ years of experience in deep learning and computer vision research * Strong programming skills in Python and experience with ...

New

Lead Allies Inc.

Research Scientist

San Francisco, CA · On-site

  • Medical

  • Dental

  • Vision

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 ...

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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 Aug 19, 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 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.

What are the key skills and qualifications needed to thrive as a climate research scientist specializing in machine learning?

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.

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 August 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.

Research Scientist - Machine Learning

Kindredventures

San Francisco, CA • On-site

$180 - $250/hr

Other

Posted yesterday

New

Job description

Overview

Extropic’s hardware massively accelerates certain kinds of probabilistic inference. Our ML team works on the science of training models in the thermodynamic paradigm, and we are looking for senior research and engineering talent to derive probabilistic ML theory, empirically demonstrate its scaling properties, and deploy performant models. Senior hires will be leading their own research direction and are therefore expected to quickly become experts across our abstraction stack, including the hardware, software, physics, and math.


Responsibilities
  • Collaborate with senior researchers, residents, engineers, and physicists to derive the theory of new probabilistic models and their learning rules, including energy-based models and diffusion models.
  • Scale up experimentation infrastructure and optimize over the design space of models.
  • Implement, visualize, and evaluate new architectures, training algorithms, and benchmarks.
  • Publish papers, contribute to open source, and communicate design insights to our hardware team.
  • Create production models for domain experts using customer data.
Required Qualifications
  • Experience in scientific Python and at least one deep learning framework (PyTorch, JAX, TensorFlow, Keras)
  • Extremely strong foundations in probability and linear algebra
  • Familiarity with deep learning theory and literature, including theory of over-parameterization and scaling laws
  • Publications in top ML conferences (NeurIPS, ICML, ICLR, CVPR)
  • Experience training high-performance models, including familiarity with infrastructure (Slurm, Ray, Weights & Biases)
  • Experience deploying models, including familiarity with infrastructure (Ray, AWS, ONNX)
Preferred Qualifications
  • Experience designing probabilistic graphical models (PGM)
  • Experience training energy-based models (EBMs) or diffusion models
  • Experience with numerical methods in diffeq solvers
  • Experience with message passing or training graph neural networks (GNNs)
  • Strong theoretical background in information geometry
  • Strong theoretical background in random matrix theory
  • Strong grasp of computational Bayesian methods, including MCMC sampling methods and variational inference

$180,000 - $250,000 a year

Salary and equity compensation will vary with experience

Extropic is an equal opportunity employer

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