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Remote Maintenance Jobs in Virginia (NOW HIRING)

Reid Agency

Remote Sales Professional

Roanoke, VA · Remote

$500 - $30K/wk

As a Remote Sales Professional, you will be responsible for identifying and pursuing new business opportunities, building and maintaining client relationships, and promoting our financial services ...

Reid Agency

Remote Sales Professional

Lynchburg, VA · Remote

$500 - $30K/wk

As a Remote Sales Professional, you will be responsible for identifying and pursuing new business opportunities, building and maintaining client relationships, and promoting our financial services ...

CGI Inc.

Remote Support Technician, Journeyman

Arlington, VA · On-site +1

$43.10K - $54.10K/yr

Remote Support Technician, Journeyman Category: Service Desk / End User Services Main location ... Maintain detailed records of issues, solutions, and user interactions. • Collaboration: Work with ...

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How much do remote maintenance jobs pay per hour?

As of May 28, 2026, the average hourly pay for remote maintenance in Virginia is $31.30, according to ZipRecruiter salary data. Most workers in this role earn between $22.88 and $37.88 per hour, depending on experience, location, and employer.

What is a Remote Maintenance job?

A Remote Maintenance job involves monitoring, diagnosing, and troubleshooting equipment, systems, or software from a remote location. This role typically includes performing routine maintenance, updating systems, and resolving technical issues without needing to be on-site. It is common in industries like IT, manufacturing, and telecommunications, where downtime must be minimized. Remote maintenance professionals use specialized tools and software to ensure smooth operation and prevent potential failures.

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

To thrive in Remote Maintenance roles, you need strong technical troubleshooting abilities, a solid understanding of mechanical or IT systems, and relevant experience or qualifications in your field (such as HVAC, networking, or industrial equipment). Familiarity with remote diagnostic tools, monitoring platforms, and certifications like CompTIA A+ (for IT) or EPA 608 (for HVAC) are often required. Excellent communication, self-motivation, and problem-solving skills set top performers apart. These combined competencies are crucial for efficiently resolving issues from a distance, minimizing downtime, and ensuring client satisfaction.

What are some common challenges faced by Remote Maintenance professionals and how can they be addressed?

Remote Maintenance professionals often encounter challenges such as diagnosing complex technical problems without being physically present and relying on digital interfaces or onsite personnel for information. To address these hurdles, strong communication and analytical skills are essential, along with familiarity with remote access software and step-by-step troubleshooting protocols. Working remotely also means staying organized, proactively managing tasks, and often coordinating with on-the-ground teams or clients. Successful Remote Maintenance professionals embrace ongoing learning to adapt to evolving technologies and keep their problem-solving skills sharp.

What job makes $10,000 a month without a degree?

Remote maintenance roles, such as specialized technical support or system administration, can pay $10,000 or more per month for experienced professionals. These jobs often require technical skills, certifications, and the ability to work independently, with some roles offering high compensation based on expertise and performance.
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Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 12 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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