ZipRecruiter

Log In

1

Climate Research Scientist Machine Learning Jobs in Reston, VA

ICF

Senior Climate Analytics Specialist

Arlington, VA

$100K - $123K/yr

Our climate risk analytics leverage rigorous science, machine learning, distributed computing, and provide clear communication to enable proactive planning and implementation of resilience solutions.

Cmu

Data Scientist

Arlington, VA

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Partner with data scientists to transition models from research/prototype into production-ready ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Partner with data scientists to transition models from research/prototype into production-ready ...

AI Squared

Machine Learning Engineer

Washington, DC

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled ... Partner with data scientists to transition models from research/prototype into production-ready ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Kitware

Machine Learning Engineer

Arlington, VA · Hybrid

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Kitware

Machine Learning Engineer

Arlington, VA · On-site

$110K - $160K/yr

Machine learning experience using visual data * Understanding of a variety of machine learning ... Kitware is a research and development software solutions provider with a mission to advance science ...

Cmu

Associate Data Scientist

Arlington, VA · On-site

$67K - $68K/yr

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

Cmu

Senior Data Scientist

Arlington, VA · On-site

Data Scientists at the SEI use advanced statistics, data analytics, machine learning, and artificial intelligence to help our government and industry clients research and solve cybersecurity ...

AISquared

Machine Learning Engineer

Washington, DC · On-site

... Machine Learning Engineer to join their core AI team. In this role, you will be responsible for ... scientists to transition models from research/prototype into production-ready deployments. • ...

next page

Showing results 1-20

All JobsClimate Research Scientist Machine Learning JobsClimate Research Scientist Machine Learning Jobs in Reston, VA

Climate Research Scientist Machine Learning information

See Reston, VA salary details

$52.5K

$135.4K

$181K

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

As of Jul 22, 2026, the average yearly pay for climate research scientist machine learning in Reston, VA is $135,368.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $180,000.00 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.

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 Reston, VA? For Climate Research Scientist Machine Learning jobs in Reston, VA, the most frequently searched job titles are:
What job categories do people searching Climate Research Scientist Machine Learning jobs in Reston, VA look for? The top searched job categories for Climate Research Scientist Machine Learning jobs in Reston, VA are:
What cities near Reston, VA are hiring for Climate Research Scientist Machine Learning jobs? Cities near Reston, VA 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 Reston, VA as of July 2026, with employment types broken down into 81% Full Time, 15% Part Time, 1% Temporary, 2% Contract, and 1% Nights. Highlights an 95% Physical, 1% Hybrid, and 4% Remote job distribution, with an average salary of $135,368 per year, or $65.1 per hour.
Machine Learning Engineer

Machine Learning Engineer

Lynker Corporation

College Park, MD • On-site, Remote

$95K - $195K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Job description

Overview
Lynker is seeking a talented and experienced Machine Learning Engineer to support the Environmental Modeling Center (EMC) within the National Centers for Environmental Prediction (NCEP). The primary objective of this role is to assist in the development of ML based systems that predict the current weather conditions everywhere given sparse observation data (this process is known as Data Assimilation [DA]). . These systems will complement existing physics-based systems and be tested as independent prototypes, running alongside traditional DA workflows. The position is located at the NOAA Center for Weather and Climate Prediction (NCWCP) in College Park, MD.
Responsibilities
Duties of the Machine Learning Engineer will include the following:
The Machine Learning Engineer will perform their job duties to a high standard, working both independently and collaboratively.The core responsibility is to assist in the development, implementation, testing, and evaluation of an AI-based Real-Time Mesoscale Analysis (AI-RTMA) system in support of NOAA's National Blend of Models (NBM). The AI-RTMA system will generate high spatial and temporal resolution analyses of meteorological variables to reduce biases in the NBM fields.. Because these fields serve as the foundation for gridded forecasts issued by the National Weather Service, this system will directly contribute to improved forecast quality.
The successful Machine Learning Engineer will work on the following scientific and engineering tasks:
  • Conduct a comprehensive review of state-of-the-art AI-based data assimilation and end-to-end weather forecasting methodologies, systems, and frameworks. Communicate findings with EMC scientists and external partners to inform the development of a scientifically robust and efficient AI-RTMA approach.
  • Collaborate with NOAA's NBM team and key stakeholders to define product requirements for AI-RTMA, including domain configuration, grid structure, output variables, spatial and temporal resolution, and data formats suitable for operational evaluation and transition.
  • Design, implement, and maintain robust data pipelines to support AI-RTMA training, validation, testing, and evaluation. This includes collecting, formatting, quality-controlling, and integrating diverse observational datasets (e.g., conventional observations, satellite, radar, and other sources), as well as preparing model inputs, targets, metadata, and training/validation splits.
  • Develop, train, rigorously test, and deploy a fully functional AI-RTMA system based on selected AI frameworks or architectures.
  • Implement cross-validation and other evaluation methodologies to quantify model performance and reliability during inference.

Qualifications
The Machine Learning Engineer selected should have the following:
  • Experience developing, training and deploying AI-based systems applied to geophysical systems.
  • Experience with common AI frameworks such as PyTorch, TensorFlow.
  • Experience working with earth observation data, including conventional observations, satellite, radar.
  • Excellent Python programming skills.
  • Practical experience utilizing High Performance Computers (HPCs) and GPUs.
  • Proven experience working in a UNIX environment with advanced scripting languages.
  • Good communication skills, both oral and written, in English.

The Ideal Machine Learning Engineer will have the following:
  • In-depth knowledge of data assimilation techniques (observation forward modeling, quality control, variational-based and/or ensemble methods).
  • Strong foundation in the physical, statistical and mathematical basis of geophysical modeling (atmospheric and/or environmental).
  • Experience with cloud platforms and use of IDEs for development.
  • Experience with cloud-native data formats such as Zarr, Parquet.
  • Experience with compiled languages.
  • Comfort using agentic AI tools to accelerate development.
  • Experience executing numerical models on HPC platforms using parallelization frameworks and job scheduling systems.
  • Familiarity with coupled earth system models.
  • Knowledge of modern software engineering practices (requirements gathering, design, prototyping, version control, integration, testing, and documentation).
  • Prior experience in model testing, evaluation, or knowledge of verification principles.

About Lynker
Lynker is a growing, employee owned business, specializing in professional, scientific and technical services. Our continually expanding team combines scientific expertise with mature, results-driven processes and tools to achieve technically sound, cost effective solutions in hydrology/water sciences, geospatial analysis, information technology, resource management, conservation, and management and business process improvement.
We focus on putting the right people in the right place to be effective. And having the right people is critical for success. Our streamlined organization enables and empowers our talented professionals to tackle our customers' scientific and technical priorities - creatively and effectively.
Lynker offers a team-oriented work environment, and the opportunity to work in a culture of exceptionally skilled professionals who embrace sound science and creative solutions. Lynker's benefits include the following:
  • Comprehensive healthcare for the employee at no monthly cost
  • Healthcare benefit covers medical, prescription drug, dental, and vision
  • Personal Time Off (PTO) Policy plus paid holidays
  • Highly competitive compensation plan regularly calibrated against industry and location benchmarks
  • 401(k) retirement plan with company-matching
  • Employee Stock Ownership Plan (ESOP) - we're all company owners!
  • Flexible spending accounts
  • Employee assistance program (EAP)
  • Short- and long-term disability insurance
  • Life and accident insurance
  • Tuition assistance/Training/Workforce improvement reimbursement per year
  • Spot bonuses for exceptional performance
  • Annual Employee Recognition Awards with bonuses
  • Employee Referral Program
  • Free centralized, self-directed Learning Management System to learn at your own pace
  • Personalized career growth plans for every employee

Lynker is an E-Verify employer.
Lynker is an equal opportunity employer and makes all employment decisions based on merit, qualifications, and business needs. We do not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, marital status, veteran status, or any other legally protected status under federal, state, or local laws.
⚠ Fraud Alert: Recruitment Scam Warning: Lynker has been made aware of fraudulent individuals posing as Lynker recruiters and offering fake job opportunities. All legitimate Lynker job postings are listed on our official careers page. Communication from Lynker recruiters will come from an official @lynker.com email address.

Apply