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Computer Vision Remote Sensing Jobs (NOW HIRING)

CACI

Staff Computer Vision AI/ML Engineer

Aurora, CO · Remote

As a CV AI/ML Engineer, you will apply cutting-edge AI/ML-based Computer Vision algorithms to problems in remote sensing, including Automatic Target Recognition (ATR) and Multimodal Data Fusion for ...

CACI

Staff Computer Vision AI/ML Engineer

Aurora, CO · Remote

As a CV AI/ML Engineer, you will apply cutting-edge AI/ML-based Computer Vision algorithms to problems in remote sensing, including Automatic Target Recognition (ATR) and Multimodal Data Fusion for ...

1872 Consulting

Sr. Computer Vision Engineer

Herndon, VA · Remote

$107K - $147K/yr

D./Master's degree in the previously mentioned fields Current knowledge of research literature in computer vision Experience working with remote sensing data, ideally satellite imagery and an ...

1872 Consulting

Sr. Computer Vision Engineer

Herndon, VA · Remote

$107K - $147K/yr

D./Master's degree in the previously mentioned fields Current knowledge of research literature in computer vision Experience working with remote sensing data, ideally satellite imagery and an ...

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Computer Vision Remote Sensing information

What is computer vision remote sensing?

Computer Vision Remote Sensing is a field that combines computer vision techniques with remote sensing data, such as satellite or aerial imagery, to automatically analyze and interpret the Earth's surface. Professionals in this area develop algorithms and models to extract useful information from images, such as land use classification, object detection, and environmental monitoring. This work supports applications in agriculture, urban planning, disaster response, and climate science by providing automated, large-scale analysis of geospatial data.

What are common challenges faced by professionals working in computer vision remote sensing projects?

Professionals in Computer Vision Remote Sensing often encounter challenges such as managing large volumes of high-resolution imagery, dealing with varying data quality, and ensuring effective preprocessing for accurate analysis. Integrating data from multiple sensors or platforms can require advanced data fusion techniques, and the need to tailor machine learning models to specific geographic or environmental contexts adds complexity. Collaboration with domain experts in fields like geography, agriculture, or environmental science is also common, as multidisciplinary teamwork is essential for interpreting results and delivering actionable insights.

What are the key skills and qualifications needed to thrive as a computer vision remote sensing specialist?

To thrive as a Computer Vision Remote Sensing specialist, you need a solid background in image processing, machine learning, and remote sensing principles, often supported by a degree in computer science, engineering, or geoinformatics. Proficiency with programming languages such as Python or MATLAB, experience with deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with GIS and satellite data processing tools are typically required. Analytical thinking, problem-solving abilities, and effective communication are crucial soft skills for interpreting data and collaborating with multidisciplinary teams. These competencies enable accurate extraction of information from remote imagery, driving innovation and informed decision-making in areas like environmental monitoring and geospatial analysis.

What is the difference between Computer Vision Remote Sensing vs Geospatial Data Analyst?

AspectComputer Vision Remote SensingGeospatial Data Analyst
Required CredentialsDegree in Remote Sensing, Computer Science, or Geospatial Technology; certifications in GIS or remote sensingDegree in Geography, GIS, or related field; certifications in GIS or spatial analysis
Work EnvironmentResearch labs, satellite data analysis, remote sensing platformsGIS offices, urban planning, environmental agencies
Industry UsageSatellite imagery analysis, environmental monitoring, defenseUrban planning, resource management, transportation

Computer Vision Remote Sensing focuses on analyzing satellite and aerial imagery using AI and computer vision techniques, often requiring specialized technical skills. In contrast, Geospatial Data Analysts interpret spatial data to support decision-making in various industries. While both roles involve geospatial data, their tools, applications, and focus areas differ significantly.

What other helpful pages are available for Computer Vision Remote Sensing?

Other pages related to Computer Vision Remote Sensing:

Infographic showing various Computer Vision Remote Sensing job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 77% Full Time, 16% Part Time, and 6% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Remote Sensing Engineer

Springfield, VA • On-site, Remote

Riverside Research Institute
See more jobs at Riverside Research Instituteexternal

$97K - $135K/yr

Full-time

Re-posted 11 days ago

Job description

Riverside Overview
Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country's most challenging technical problems.
All Riverside Research opportunities require U.S. Citizenship.
Position Overview
We are seeking a skilled Remote Sensing Engineer to support the development, analysis, and exploitation of remote sensing data for national security, defense, and geospatial intelligence missions. The ideal candidate has experience working with geospatial datasets, remote sensing technologies, and automation tools, and is comfortable collaborating across multidisciplinary teams to solve complex technical challenges.
An active Top Secret/Sensitive Compartmented Information (TS/SCI) clearance is required for this position.
Responsibilities
  • Process, analyze, and interpret satellite, airborne, and other remotely sensed imagery.
  • Develop and maintain geospatial analysis workflows and automated processing pipelines.
  • Design and implement Python-based tools to support imagery processing, feature extraction, and geospatial analysis.
  • Perform image classification, object detection, change detection, and spatial analysis using commercial and open-source tools.
  • Support sensor calibration, validation, and quality assurance activities.
  • Work closely with engineers, data scientists, and intelligence analysts to develop mission-focused solutions.
  • Prepare technical documentation, reports, and presentations for technical and non-technical audiences.
  • Evaluate emerging remote sensing technologies and recommend improvements to existing workflows.
  • Contribute to project planning, technical discussions, and continuous process improvement initiatives.

Qualifications
Required Qualifications
  • Active TS/SCI security clearance (required).
  • Bachelor's degree in Remote Sensing, Geospatial Science, Geography, GIS, Computer Science, Engineering, Physics, Environmental Science, or a related technical discipline.
  • minimum of 5 years professional experience in remote sensing, geospatial analysis, GIS, or a related engineering field.
  • Experience processing and analyzing satellite, aerial, or other remotely sensed imagery.
  • Proficiency with remote sensing and GIS software such as ArcGIS Pro, QGIS, ENVI, ERDAS Imagine, or similar platforms.
  • Strong Python programming skills for geospatial analysis and workflow automation.
  • Experience with geospatial libraries such as GDAL, Rasterio, GeoPandas, Shapely, or OpenCV.
  • Understanding of raster and vector geospatial data formats and coordinate reference systems.
  • Strong analytical, problem-solving, and communication skills.
  • Ability to manage multiple priorities and work independently in a remote, collaborative environment.
Preferred Qualifications
  • Experience supporting DoD, NGA, NRO, or Intelligence Community programs.
  • Experience with SAR, LiDAR, hyperspectral, multispectral, or thermal imagery.
  • Familiarity with cloud-based geospatial processing environments such as AWS or Azure.
  • Experience with machine learning or computer vision techniques applied to geospatial imagery.
  • Knowledge of containerization technologies such as Docker and modern software development practices.
  • Experience with Git and collaborative software development workflows.

Global Comp
$97,000 - $135,000 This represents the typical compensation range for this position based on experience, location and other factors.
Closing Statement
Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees.
Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran's status or any other status legally protected by applicable federal, state, and local law.

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