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Climate Research Scientist Machine Learning Jobs

Role As a Machine Learning Research Scientist, you will lead groundbreaking ML research and development at SmarterDx, collaborating closely with experienced engineers and clinicians to turn your ...

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

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 ...

Senior Machine Learning Scientist

Austin, TX · On-site

$97K - $124K/yr

Your Impact The Senior Machine Learning Research Scientist is a key contributor to DISCO's machine learning and AI research initiatives, leading the development of advanced algorithms and ...

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

As of Jun 19, 2026, the average yearly pay for climate research scientist machine learning in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 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.

Is AI working on climate change?

Climate research scientists using machine learning develop AI models to analyze climate data, improve climate predictions, and identify patterns related to environmental change. These applications help inform policy decisions and support climate mitigation efforts, making AI a valuable tool in addressing climate change challenges.

Are climate scientists in demand?

Climate research scientists with expertise in machine learning are in increasing demand due to the growing focus on climate change mitigation and adaptation. Employers seek professionals skilled in data analysis, modeling, and environmental science, often requiring proficiency in programming languages like Python or R. Job opportunities are available in academia, government agencies, and private sector organizations working on climate-related projects.

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.

Will AI replace data scientists in 2050?

As a Climate Research Scientist with machine learning expertise, AI is expected to augment rather than replace data scientists by automating routine tasks and providing advanced analytical tools. Human judgment, domain knowledge, and interpretative skills will remain essential for complex problem-solving and decision-making in data science roles through 2050.

What is the average salary of a Climate Scientist?

The average salary of a Climate Research Scientist varies by experience and location but typically ranges from $60,000 to $100,000 annually. Those with advanced degrees, specialized skills in machine learning, and experience in data analysis tend to earn higher salaries within this field.

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.

More about Climate Research Scientist Machine Learning jobs
What cities are hiring for Climate Research Scientist Machine Learning jobs? Cities with the most Climate Research Scientist Machine Learning job openings:
What states have the most Climate Research Scientist Machine Learning jobs? States with the most job openings for Climate Research Scientist Machine Learning jobs include:
What job categories do people searching Climate Research Scientist Machine Learning jobs look for? The top searched job categories for Climate Research Scientist Machine Learning jobs are:
Infographic showing various Climate Research Scientist Machine Learning job openings in the United States as of June 2026, with employment types broken down into 98% Full Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.
Research Scientist - RF Machine Learning

Research Scientist - RF Machine Learning

Peraton

College Park, MD • On-site

Full-time

Posted 9 days ago


Peraton rating

8.2

Company rating: 8.2 out of 10

Based on 53 frontline employees who took The Breakroom Quiz

45th of 204 rated it services


Job description

Responsibilities

Peraton Labs is seeking a poly cleared Senior Research Scientist to support cleared research and development efforts for a Maryland-based IC customer. This role will focus on leading the design, development, prototyping, and evaluation of RF Machine Learning algorithms and signal processing techniques for advanced wireless, spectrum, cyber, and communications research.

You'll work on mission-focused R&D efforts that move from research concepts to working prototypes and operationally relevant capabilities. You will collaborate with researchers, software engineers, signal processing experts, and customer stakeholders to solve complex problems involving RF sensing, signal characterization, waveform analysis, spectrum awareness, and machine learning-enabled wireless systems.

This position requires full-time on-site work at a customer site near College Park, MD.

Key responsibilities may include

  • Lead the design, development, prototyping, and evaluation of RF/ML algorithms for wireless, spectrum, and communications applications
  • Research and implement machine learning approaches for RF signal detection, classification, characterization, anomaly detection, emitter identification, spectrum sensing, or waveform analysis
  • Develop and evaluate algorithms using modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, JAX, or similar tools
  • Apply strong digital signal processing and RF domain knowledge to develop, train, test, and validate models against real-world or simulated RF data
  • Design data collection, labeling, preprocessing, feature extraction, training, evaluation, and experimentation workflows for RFML research
  • Develop software prototypes using Python, C/C++, MATLAB, GNU Radio, or similar tools
  • Analyze RF signals, wireless protocol behavior, modulation characteristics, channel effects, interference, noise, and system performance
  • Work with RF datasets, signal captures, IQ data, SDR platforms, and lab or field-collected spectrum data
  • Support integration of RFML capabilities into larger research prototypes, testbeds, cyber experimentation platforms, or operationally relevant systems
  • Communicate research findings, technical approaches, experiment results, and prototype capabilities through customer briefings, technical reports, whitepapers, and publications
  • Provide technical leadership, mentor junior researchers or engineers, and help shape future RFML research direction

*This position may be eligible for an increased sign-on bonus. Eligibility, bonus amount, and applicable terms and conditions will be discussed during the recruiting process*

#MDFSP

#PLABS26

Qualifications

Minimum Qualifications

  • Minimum of 6+ years of experience with a Bachelor's degree, 4+ years of experience with a Master's degree, or 2+ years of experience with a Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related discipline. In lieu of a Bachelors, an additional 4 years of experience is required for a total of 10+ years.
  • Strong background in Radio frequency Machine Learning, digital signal processing, wireless communications, or RF systems research
  • Experience designing, developing, training, testing, or evaluating machine learning models for RF, wireless, spectrum, signal processing, or communications applications
  • Experience with modern machine learning frameworks such as PyTorch, TensorFlow, Keras, scikit-learn, or similar tools
  • Strong Experience programming in Python and at least one additional language such as C/C++, Java, or similar
  • Experience working with RF data, signal captures, IQ samples, simulated waveforms, or real-world wireless datasets
  • Experience working in Linux-based dev environments
  • Ability to develop, test, troubleshoot, document, and demonstrate research prototypes
  • Strong written and verbal communication skills, including the ability to present technical concepts and research results to technical stakeholders
  • US Citizenship is a requirement for this position
  • This position requires an active/current TS/SCI w/ Polygraph

Desired Additional Qualifications

  • Advanced degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, Physics, or a related technical field is preferred
  • Demonstrated history of research in Machine Learning and RF spectrum domains, including publications, prototypes, proposals, patents, technical reports, or customer-facing research briefings
  • Experience with RFML applications such as signal classification, modulation recognition, emitter identification, spectrum sensing, anomaly detection, interference detection, protocol inference, or RF fingerprinting
  • Experience with SDR platforms such as Ettus USRP, HackRF, BladeRF, LimeSDR, or similar hardware
  • Familiarity with SDR software and RF development tools such as GNU Radio, UHD/USRP, MATLAB, Simulink or similar tools
  • Experience with wireless systems or protocols such as LTE, 5G, Wi-Fi, SATCOM, MANET, tactical radio systems, mesh networks, or custom waveform environments
  • Experience with RF test equipment such as spectrum analyzers, signal generators, oscilloscopes, vector signal analyzers, channel emulators, or RF front-end equipment
  • Experience with deep learning approaches for signal processing, including CNNs, RNNs, transformers, autoencoders, contrastive learning, self-supervised learning, or generative models
  • Experience with data engineering for RFML, including dataset generation, augmentation, labeling, synthetic data, simulation, model evaluation, and experiment tracking
  • Experience with tools such as NumPy, SciPy, Pandas, cuSignal, CUDA, MLflow, Weights & Biases, DVC, or similar tools
  • Experience integration ML models into deployable prototypes, edge systems, containers, testbeds, or cyber/radio experimentation environments
  • Experience with RF cyber research, wireless security, electronic warfare, spectrum operations, protocol reverse engineering, or adversarial ML
  • Ability to serve as a technical lead, task lead, or principal investigator on DoD/IC research efforts
Peraton Overview

Peraton is a next-generation national security company that drives missions of consequence spanning the globe and extending to the farthest reaches of the galaxy. As the world's leading mission capability integrator and transformative enterprise IT provider, we deliver trusted, highly differentiated solutions and technologies to protect our nation and allies. Peraton operates at the critical nexus between traditional and nontraditional threats across all domains: land, sea, space, air, and cyberspace. The company serves as a valued partner to essential government agencies and supports every branch of the U.S. armed forces. Each day, our employees do the can't be done by solving the most daunting challenges facing our customers. Visit peraton.com to learn how we're keeping people around the world safe and secure.

Target Salary Range$135,000 - $216,000. This represents the typical salary range for this position. Salary is determined by various factors, including but not limited to, the scope and responsibilities of the position, the individual's experience, education, knowledge, skills, and competencies, as well as geographic location and business and contract considerations. Depending on the position, employees may be eligible for overtime, shift differential, and a discretionary bonus in addition to base pay.EEOEEO: Equal opportunity employer, including disability and protected veterans, or other characteristics protected by law.Employment Type: FULL_TIME

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About Peraton

Sourced by ZipRecruiter

At Peraton, we re at the forefront of delivering the next big thing every day. We re the partner of choice to help solve some of the world s most daunting challenges, delivering bold, new solutions to keep people around the world safer and more secure.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Herndon, VA, US

Year founded

2017