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Remote Design Researcher Jobs in Virginia (NOW HIRING)

Sentara

Research Analytics Remote-Intern

Norfolk, VA · Remote

This position is fully remote! Overview The Intern position serves as an educational development ... Research Design & Planning:Assists in development of study design, analytic plans, and research ...

For People

Senior UX Researcher (Contract)

Arlington, VA · On-site +1

$100K - $130K/yr

Our entire team is remote across the United States, from the West Coast to the East Coast. There ... design in real user need rather than reference architecture. * Co-author the discovery's research ...

New

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Design and implement data-driven solutions, with specific focus on advanced analytical methods ... Requirements: * MUST HAVE Six (6) years of relevant experience in applied research, big data ...

Elder Research

Data Scientist (Remote)

Arlington, VA · On-site +1

Design and implement data-driven solutions, with specific focus on advanced analytical methods ... Requirements: * MUST HAVE Six (6) years of relevant experience in applied research, big data ...

Delaware Nation Industries

Customer Experience

Arlington, VA · On-site +1

$18.50 - $25/hr

... remote testing, concept testing, and survey design in order to design customer research methods to measure customer experience feedback; and to identify trends in new methods from industry and ...

Hyphen Connect Limited

$162.10K - $199.20K/yr

Collaborate effectively with engineering, product, QA, and research teams to ensure design ... REMOTE

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How much do remote design researcher jobs pay per year?

As of May 29, 2026, the average yearly pay for remote design researcher in Virginia is $112,132.00, according to ZipRecruiter salary data. Most workers in this role earn between $66,400.00 and $152,700.00 per year, depending on experience, location, and employer.

What is a Remote Design Researcher job?

A Remote Design Researcher is responsible for studying user needs, behaviors, and experiences to inform design decisions, all while working remotely. They conduct user interviews, usability testing, and data analysis to improve digital products and services. This role requires strong analytical skills, empathy, and expertise in research methodologies. By working remotely, they collaborate with designers, product managers, and stakeholders using digital tools. The goal is to ensure that design solutions align with user expectations and business objectives.

What are the key skills and qualifications needed to thrive in the Remote Design Researcher position, and why are they important?

To thrive as a Remote Design Researcher, you need a solid background in user research methods, human-centered design principles, and data analysis, typically backed by a degree in design, psychology, or a related field. Familiarity with tools such as Figma, Miro, Dovetail, and survey platforms, along with UX research certifications, is often expected. Outstanding communication skills, self-motivation, and the ability to collaborate effectively across distributed teams are highly valued soft skills. These competencies are essential for gathering actionable insights, driving design decisions, and ensuring remote research processes are effective and impactful.

What are some common challenges faced by Remote Design Researchers, and how do they overcome them?

Remote Design Researchers often face challenges such as coordinating research sessions across different time zones, building rapport with participants virtually, and collaborating effectively with design and product teams from a distance. To overcome these, they typically rely on clear communication channels, organized project management tools, and video conferencing software to facilitate real-time feedback and engagement. They also develop strong documentation and reporting practices to ensure research findings are accessible and actionable for team members. Adapting research techniques to the remote context, such as remote usability testing and asynchronous interviews, helps them gather quality insights despite the physical distance.
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Remote Design Researcher jobs near you

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 13 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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