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What are the key skills and qualifications needed to thrive as a Live-In Remote Health Science professional, and why are they important?

To excel as a Live-In Remote Health Science professional, you need a solid background in health sciences, patient care, and relevant certifications such as CPR or other health-related credentials. Familiarity with telehealth platforms, remote monitoring devices, and digital health records is often required. Strong communication, self-motivation, and adaptability are essential soft skills for building trust and effectively supporting patients remotely. These qualifications ensure safe, effective care and seamless coordination in remote or underserved environments.

What are some unique challenges faced by professionals in Live-In Remote Health Science roles, and how can one prepare for them?

Live-In Remote Health Science professionals often work in isolated settings, such as rural communities, research stations, or remote clinics, which can lead to challenges like limited immediate access to specialist support and resources. Adapting to varying levels of infrastructure and managing diverse health needs independently are common aspects of the role. Successful candidates prepare by developing strong problem-solving skills, self-sufficiency, and the ability to communicate effectively with off-site colleagues. Building resilience and maintaining professional networks are also key to thriving in this environment.

What is a Live In Remote Health Science professional?

A Live In Remote Health Science professional is a healthcare worker who resides within a remote or rural community to provide essential health services. These professionals may include nurses, doctors, or allied health workers who address local health needs, often in areas with limited access to medical facilities. Their responsibilities typically include patient care, health education, disease prevention, and sometimes emergency response. They play a crucial role in improving healthcare outcomes in underserved regions by ensuring continuous health support.

What is the difference between Live In Remote Health Science vs Remote Health Science?

AspectLive In Remote Health ScienceRemote Health Science
Work EnvironmentTypically involves living onsite or nearby, with some remote workPrimarily work from home or remote locations without onsite requirements
CredentialsRequires health science certifications, licenses, and possibly live-in arrangementsRequires similar credentials but less emphasis on onsite living
Employer & Industry UsageUsed in healthcare facilities, research centers, or clinics offering live-in optionsCommon in telehealth, research, and consulting roles in health sciences

Live In Remote Health Science involves a combination of onsite living and remote work, often requiring specific certifications and a live-in arrangement. Remote Health Science typically allows professionals to work entirely remotely, focusing on telehealth or research roles without onsite commitments. Both roles require health science credentials but differ mainly in work environment and living arrangements.

What cities in Virginia are hiring for Live In Remote Health Science jobs? Cities in Virginia with the most Live In Remote Health Science job openings:
Live In Remote Health Science jobs near you
Infographic showing various Live In Remote Health Science job openings in Virginia as of May 2026, with employment types broken down into 5% Internship, 42% Full Time, 37% Part Time, and 16% Contract. Highlights an 58% In-person, and 42% Remote job distribution.

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 16 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
Riverside Research's Cognitive Intelligence Solutions Group (CISG) is seeking a Remote Sensing Engineer to support cutting-edge geospatial intelligence, autonomous sensing, and AI/ML-driven data exploitation efforts for the U.S. Department of Defense and Intelligence Community. The successful candidate will serve as a technical lead responsible for the automated verification and validation (V&V), test and evaluation (T&E), and performance assessment of remote sensing data pipelines, AI/ML models, and third-party vendor capabilities. This role bridges rigorous scientific methodology with production-grade engineering, enabling CISG to deliver validated, mission-ready geospatial intelligence products. The ideal candidate combines deep expertise in multispectral and hyperspectral remote sensing with hands-on experience applying machine learning to operational geospatial workflows.
This position is located in Fairfax, VA.
#LI-Onsite
Responsibilities
  • Design, develop, and implement automated V&V and T&E frameworks to assess the accuracy, performance, and operational readiness of remote sensing data products, AI/ML models, and vendor-delivered geospatial capabilities.
  • Lead the technical evaluation of commercial and government remote sensing platforms, sensors (multispectral, hyperspectral, SAR, LiDAR), and associated data products against mission-specific requirements.
  • Develop and maintain scalable, production-grade machine learning pipelines for geospatial applications including change detection, land cover classification, object detection, and environmental monitoring.
  • Apply state-of-the-art AI/ML techniques - including deep learning, transfer learning, self-supervised learning, and large vision/language models - to automate remote sensing data exploitation and analysis workflows.
  • Conduct rigorous uncertainty quantification, validation metric development, and statistical performance benchmarking across multi-source, multi-temporal geospatial datasets.
  • Architect and execute data quality assessment (DQA) protocols for ingested satellite, airborne, and in-situ sensor data; document and communicate findings to program teams and stakeholders.
  • Collaborate with program managers, government customers, and interdisciplinary engineering teams to translate operational requirements into validated technical solutions.
  • Evaluate and integrate emerging remote sensing technologies and open-source AI/ML frameworks; assess vendor claims, algorithm documentation, and technical data packages.
  • Contribute to IRAD initiatives advancing CISG's remote sensing and autonomous sensing capabilities, including development of novel approaches for environmental monitoring, target detection, and geospatial change analytics.
  • Author technical reports, white papers, and briefings documenting methodology, V&V results, and performance findings for government sponsors.
  • Provide technical mentorship to junior engineers and researchers on remote sensing methods, ML best practices, and geospatial data science.
  • Stay current with advances in foundation models, multi-modal geospatial AI, and emerging remote sensing sensor modalities relevant to national security applications.

Qualifications
Required Qualifications:
  • Active U.S. Citizenship (required for all Riverside Research positions).
  • Must be able to obtain and maintain a Top Secret security clearance with SCI access; ability to obtain program-specific clearances as required. Candidates with an active TS/SCI are strongly preferred.
  • Bachelor's degree in Remote Sensing, Geospatial Science, Earth Systems, Electrical Engineering, Computer Science, or a closely related STEM field.
  • A minimum of 8 years of related experience with a Bachelor's degree, 6 years with a Master's degree, 3 years with a PhD, or equivalent combination of education and experience. Graduate research experience counts toward this threshold.
  • Demonstrated expertise in multispectral and/or hyperspectral remote sensing data analysis, including atmospheric correction, spectral indices, spectral unmixing, and feature extraction.
  • Proficiency in Python for geospatial data engineering, including experience with rasterio, rioxarray, xarray, GDAL, geopandas, NumPy, and scikit-learn.
  • Hands-on experience with machine learning and statistical modeling applied to remote sensing or geospatial datasets (e.g., classification, regression, anomaly detection, change detection).
  • Experience developing and executing V&V or T&E processes for data products, software systems, or AI/ML models, including design of test plans, performance metrics, and acceptance criteria.
  • Familiarity with geospatial platforms and tools: ArcGIS Pro, QGIS, ENVI, and/or Google Earth Engine.
  • Experience with cloud-based geospatial workflows (AWS, Google Cloud, or Azure) and version control practices (Git/GitLab/GitHub).
  • Strong written and verbal communication skills with demonstrated ability to present complex technical findings to both technical and non-technical audiences.

Desired / Preferred Qualifications:
  • Active Top Secret/SCI clearance - candidates who already hold an active TS/SCI will be given strong preference and can expect an accelerated onboarding timeline.
  • Experience supporting DoD, Intelligence Community, or national security remote sensing programs (NRO, NGA, AFRL, ARO, or equivalent).
  • Familiarity with hyperspectral sensing platforms (e.g., AVIRIS, PRISMA, orbital hyperspectral systems) and hyperspectral analytics pipelines including mineral characterization and vegetation health assessment.
  • Experience applying deep learning frameworks (PyTorch, TensorFlow, Hugging Face) to geospatial or computer vision tasks, including fine-tuning foundation models or geospatial FMs (e.g., Prithvi, SatMAE, Clay).
  • Background in SAR processing, LiDAR analysis, or multi-modal sensor fusion for environmental or intelligence applications.
  • Experience with automated testing frameworks, CI/CD pipelines, and MLOps practices for geospatial AI/ML systems.
  • Track record of peer-reviewed publication, conference presentations (e.g., IGARSS, AGU, SPIE), or technical reports in remote sensing or geospatial AI.
  • Demonstrated experience in a lead or senior individual contributor role, including mentorship of junior technical staff and coordination across multi-disciplinary teams.
  • Familiarity with GEOINT tradecraft, NSDI standards, or DoD geospatial data standards (NTM, NITF, STANAG imagery formats).

Global Comp
$115,000 - $200,000 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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