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Remote Chemical Process Engineer Jobs in Reston, VA

Career Renew

AI Strategy and Process Lead

Washington, DC · Remote

$140K - $220K/yr

Career Renew is recruiting for one of its clients an AI Strategy and Process Lead - this is a fully remote role for US-based candidates. Salary range: 140-220K USD yearly plus benefits plus equity.

ICF

On Call Critical Minerals Expert - Remote

Washington, DC · On-site +1

$20.50 - $21/hr

Processing, separation, refining, and metallurgy innovation * Battery, magnet, and advanced ... engineering, chemical engineering, environmental engineering, earth sciences, or a related ...

VetsEZ

DevSecOps Engineer (Remote Opportunity)

Washington, DC · Remote

$59.75 - $81.75/hr

We are currently looking for a DevSecOps Engineer for a 100% remote position on a large federal ... Participate in incident response efforts, root cause analysis, and continuous process improvement ...

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Remote Chemical Process Engineer information

See Reston, VA salary details

$47.3K

$105.4K

$168.5K

How much do remote chemical process engineer jobs pay per year?

As of May 31, 2026, the average yearly pay for remote chemical process engineer in Reston, VA is $105,412.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,800.00 and $119,100.00 per year, depending on experience, location, and employer.

What is a Remote Chemical Process Engineer job?

A Remote Chemical Process Engineer designs, analyzes, and optimizes chemical manufacturing processes while working from a remote location. They use simulation software, data analysis, and virtual collaboration tools to improve efficiency, safety, and sustainability in chemical production. Responsibilities may include process design, troubleshooting, scaling operations, and ensuring regulatory compliance. Remote engineers often coordinate with on-site teams, suppliers, and clients through digital communication. This role requires strong problem-solving skills and expertise in chemical engineering principles to enhance industrial processes effectively.

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

To thrive as a Remote Chemical Process Engineer, you need a solid background in chemical engineering principles, process design, and troubleshooting, typically supported by a relevant engineering degree and professional certifications like a PE or EIT. Familiarity with process simulation software (such as Aspen Plus or HYSYS), data analysis tools, and remote collaboration platforms is important. Strong problem-solving skills, effective time management, and clear communication are essential for working autonomously and collaborating with distributed teams. These skills ensure efficient process optimization, regulatory compliance, and seamless teamwork despite remote work settings.

What are some typical daily responsibilities for a Remote Chemical Process Engineer?

As a Remote Chemical Process Engineer, your day-to-day tasks often include analyzing process data, designing or optimizing chemical processes, creating technical documentation, and troubleshooting operational issues. You'll regularly use process simulation software and collaborate virtually with cross-functional teams such as project managers, plant operators, and safety specialists. Participation in virtual meetings, providing technical support, and ensuring compliance with safety and environmental regulations are also common parts of the job. This role requires managing your own schedule efficiently while staying responsive to the needs of both internal and external stakeholders.
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Remote Chemical Process Engineer jobs near you

Remote Sensing Engineer

Riverside Research Institute

Fairfax, VA • On-site, Remote

$150K - $180K/yr

Full-time

Posted 15 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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