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Remote Geolocation Jobs (NOW HIRING)

Classic Reach and Aggregate Remote Capability (ARC). * Finder Family of Systems. * Digital Receiver ... Multiplatform Geolocation (MPG) with JICD 4.2. Compensation Details: US: $140,000 to $155,000 The ...

GEOINT Analyst Mid

Charlottesville, VA ยท Remote

$110K - $150K/yr

Provides non-literal analysis to produce intelligence products, using remote sensing methodologies ... geolocation indicators, legend, title, classification, and projection information * Ability to ...

Technical Program Manager

Herndon, VA ยท On-site +1

$132K - $171K/yr

RF/Signal Experience: Exposure to RF signal processing, geolocation, spectrum monitoring, or ... Geospatial analytics, remote sensing, or high-throughput data platforms. Benefits A compensation ...

Senior Software Engineer

$125K - $165K/yr

... remote. We do not hire based on buzzwords or popular acronyms. We expect you to have mastered at ... Solve advanced mapping and geolocation problems. * Build out our public RESTful API. * Review ...

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Remote Geolocation information

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$72K

$120.8K

$158K

How much do remote geolocation jobs pay per year?

As of Jul 1, 2026, the average yearly pay for remote geolocation in the United States is $120,809.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,000.00 and $141,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Geolocation Specialist, and why are they important?

To thrive as a Remote Geolocation Specialist, you need strong analytical skills, proficiency in GIS (Geographic Information Systems), and a relevant degree in geography, geoinformatics, or a related field. Familiarity with tools such as ArcGIS, QGIS, GPS technology, and remote sensing software is typically required, and certifications like GISP can be advantageous. Attention to detail, problem-solving abilities, and effective communication help specialists interpret data accurately and collaborate with cross-functional teams. These skills ensure precise location data analysis, support decision-making, and enhance the reliability of geolocation solutions.

What are some common challenges faced by professionals working in remote geolocation roles?

Professionals in remote geolocation roles often encounter challenges related to data accuracy and connectivity, especially when working with real-time location data from diverse sources. Ensuring the precision of geospatial data while collaborating across distributed teams can require strong communication and coordination skills. Additionally, adapting to rapidly changing technologies and maintaining up-to-date knowledge of mapping tools and geolocation standards is essential for continued success in the field.

What is the difference between Remote Geolocation vs Remote Network Technician?

AspectRemote GeolocationRemote Network Technician
Required CredentialsGeolocation certifications, GPS technology knowledgeNetworking certifications (e.g., CompTIA Network+), IT skills
Work EnvironmentLocation-based data analysis, GPS toolsRemote troubleshooting, network setup, and maintenance
Employer & Industry UsageLogistics, mapping, location servicesIT, telecommunications, corporate networks
Search & Comparison IntentUnderstanding geolocation services remotelyRemote network troubleshooting roles

Remote Geolocation focuses on analyzing location data and GPS technology, often within logistics or mapping industries. Remote Network Technicians handle network setup, troubleshooting, and maintenance remotely, primarily in IT and telecommunications. While both roles can be performed remotely, they require different skill sets and certifications. The comparison helps job seekers identify the right role based on their expertise and industry focus.

What is remote geolocation?

Remote geolocation refers to the process of determining the physical location of a device, person, or object without direct contact, usually through the use of GPS, Wi-Fi, IP addresses, or cellular networks. Professionals in this field analyze data from various remote sensing technologies to pinpoint or track locations globally. Remote geolocation is widely used in applications such as navigation, asset tracking, emergency response, and location-based services. It plays a critical role in industries like logistics, security, and telecommunications.
What cities are hiring for Remote Geolocation jobs? Cities with the most Remote Geolocation job openings:
What are the most commonly searched types of Geolocation jobs? The most popular types of Geolocation jobs are:
What states have the most Remote Geolocation jobs? States with the most job openings for Remote Geolocation jobs include:
Infographic showing various Remote Geolocation job openings in the United States as of June 2026, with employment types broken down into 94% Full Time, and 6% Part Time. Highlights an 89% Physical, 5% Hybrid, and 6% Remote job distribution, with an average salary of $120,809 per year, or $58.1 per hour.
Principal Scientist AI/ML Specialization - WFH1651 (Remote)

Principal Scientist AI/ML Specialization - WFH1651 (Remote)

Global InfoTek, Inc.

Reston, VA โ€ข Remote

Full-time

Posted 2 days ago

Be an early applicant


Job description

Clearance Level:

US Citizenship: Required

Job Classification: Full Time

Location: Remote

Years of Experience: 10+ years of relevant experience

Education Level: Advanced degree (MS or PhD) in Electrical Engineering, Computer Science, Applied Mathematics, or a closely related quantitative field. Experience may be considered in place of education requirement.

Briefly Describe the Work:

GITI is seeking a Principal Scientist to serve as the senior technical authority on an R&D program focused on passive RF emitter identification and network analysis from real-time sensor data streams. The Principal Scientist leads independent, hands-on analysis of NDF (Network Description File) sensor datasets, provides technical direction across parallel research threads, and serves as the primary technical advisor to the government sponsor. The role spans the full research lifecycle: formulating hypotheses, writing and executing analytical code in Python and Jupyter notebooks, interpreting and validating results, and communicating findings to both technical peers and non-specialist stakeholders. This is a deeply technical, hands-on position the Principal Scientist conducts analysis directly and does not delegate technical work as a substitute for personal proficiency. The candidate will work within a small, distributed team operating in air-gapped Linux environments on resource-constrained tactical edge hardware, with no cloud computing.

Responsibilities:

  • Conduct independent, hands-on data analysis on RF sensor datasets using Python and Jupyter notebooks formulating hypotheses, writing and running analytical code, interpreting results, and producing findings that directly advance program research objectives
  • Provide technical advice and research direction across a multidisciplinary team; define analytical objectives, review and validate technical outputs from AI/ML engineers and software developers, and ensure coherence across parallel research threads
  • Serve as primary technical advisor to the government sponsor: translate operational requirements into research objectives, communicate findings clearly to non-specialist stakeholders, and maintain program alignment with sponsor priorities through written reports and technical presentations
  • Design and execute analytical investigations into RF sensor data quality, emitter behavior, and attribution reliability including characterizing error sources, identifying systematic artifacts, and developing methods to distinguish real physical signatures from sensor or processing artifacts
  • Produce technical documentation working notes, research findings, monthly status reports, and briefing materials that accurately represent the scope and confidence level of analytical results

Expert-level career professional recognized as a technical authority in RF systems, signals intelligence, or a closely related applied domain. Exercises broad independent judgment in defining research approach, evaluating methods, and interpreting results. Operates with minimal supervision; accountable for the scientific integrity and practical relevance of program research outputs. Advanced degree (MS or PhD) with 10+ years of hands-on applied R&D experience.

Required Skills:

  • 10+ years of hands-on applied R&D experience in RF systems, signals intelligence, electronic warfare, or related domains.
  • Proven ability to quickly acquire domain knowledge; specifically in the areas of wireless digital communications and military techniques, tactics, and procedures
  • Demonstrated ability to independently develop and execute data analyses in Python or equivalent tools on real sensor datasets; must be capable of writing production-quality analytical code, not merely directing others to do so
  • Experience addressing common problems with large quantities of real-world data, such as imputation, noise, bias, and errors
  • Track record of working effectively on constrained-hardware edge systems no cloud, no discrete GPU with attention to computational efficiency and multi-core, multi-thread performance on x86 platforms

Desired Skills:

  • Deep familiarity with RF signal characteristics, sensor phenomenology, and the interpretation of passive receiver data including recognition of processing artifacts, attribution ambiguities, and the limits of sensor-derived measurements
  • Hands-on experience applying machine learning particularly metric learning, deep learning networks, or similarity-learning architectures to RF or time-series signal data, including feature engineering, training pipeline development, and model validation
  • Familiarity with TDMA network protocols, emitter identification techniques (CID/PID), and the signal processing challenges of dense, contested electromagnetic environments
  • Experience with interferometric direction-finding, TDOA geolocation, or related passive geolocation methods, including practical knowledge of their failure modes and accuracy limitations
  • Experience with binary serialization formats (FlatBuffers, Protocol Buffers) and high-throughput sensor data pipelines operating in near-real-time on resource-constrained hardware
  • Background in statistical signal processing error ellipses, bearing estimation uncertainty, feature reliability under noise with the ability to distinguish statistically significant findings from artifacts of small sample size or improper normalization

Relevant Certifications:

  • Professional certifications in data science, signal processing, or related technical fields. Advanced academic credentials (PhD, MS) in a relevant quantitative discipline are strongly preferred and may substitute for certifications.

Global InfoTek, Inc. is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability.

About Global InfoTek, Inc. Global InfoTek Inc. has an award-winning track record of designing, developing, and deploying best-of-breed technologies that address the nation's pressing cyber and advanced technology needs. GITI has rapidly merged pioneering technologies, operational effectiveness, and best business practices for over two decades.