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Remote Grader Jobs in Washington (NOW HIRING)

BlazerJobs

SLP Remote in MD

Silver Spring, MD · Remote

$42.13 - $59.71/hr

Providing virtual speech-language pathology services to K-12 students, with caseloads varying by grade level and skillset, including up to 40 elementary, 48 middle, and 57 at peak. * Collaborating ...

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Saga Education

Remote Math Tutor

Oxon Hill, MD · Remote

$18 - $21.65/hr

Remote; Full-time Schedule: Monday - Friday; 37.5 hours/week (during traditional school hours ... Rigorous research shows that high-impact tutoring raises grades and builds student confidence and a ...

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How much do remote grader jobs pay per hour?

As of May 28, 2026, the average hourly pay for remote grader in Washington is $19.35, according to ZipRecruiter salary data. Most workers in this role earn between $13.08 and $22.88 per hour, depending on experience, location, and employer.

What is a Remote Grader job?

A Remote Grader evaluates and scores assignments, exams, or coursework submitted by students, typically for online or distance learning programs. They follow specific grading rubrics provided by the institution or instructor to ensure consistency and fairness. This role often requires subject matter expertise, attention to detail, and the ability to provide constructive feedback. Remote Graders typically work independently and communicate with instructors or educational institutions as needed.

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

To thrive as a Remote Grader, you need a strong command of subject matter expertise, attention to detail, and the ability to evaluate assignments fairly, typically supported by relevant academic credentials or teaching experience. Familiarity with online grading platforms, learning management systems (LMS), and digital assessment tools is often required for effective and efficient work. Strong time management, clear written communication, and self-motivation are essential soft skills for this independent, deadline-driven role. These skills and qualities are critical for maintaining grading accuracy, meeting turnaround expectations, and supporting student learning outcomes remotely.

What are some common challenges faced by Remote Graders, and how can they be addressed?

Remote Graders often encounter challenges such as managing a high volume of submissions during peak periods, maintaining consistency and objectivity in grading, and balancing flexible hours with strict deadlines. Working independently can also require strong self-discipline and effective organization to stay on top of grading tasks. To address these challenges, it's helpful to establish a regular grading schedule, leverage built-in analytics or rubrics provided by the LMS, and communicate with supervisors or fellow graders when clarification or support is needed. Proactively reaching out for feedback and ongoing training can also help Remote Graders improve their performance and adapt to changing expectations.
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What job categories do people searching Remote Grader jobs in Washington look for? The top searched job categories for Remote Grader jobs in Washington are:
What cities in Washington are hiring for Remote Grader jobs? Cities in Washington with the most Remote Grader job openings:
Remote Grader jobs near you
Infographic showing various Remote Grader job openings in Washington as of May 2026, with employment types broken down into 62% Full Time, 19% Part Time, and 19% Contract. Highlights an 44% In-person, 6% Hybrid, and 50% Remote job distribution, with an average salary of $40,246 per year, or $19.3 per hour.

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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