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Remote Geospatial Developer Jobs in Ohio (NOW HIRING)

Systems Engineer

Dayton, OH ยท On-site +1

This role is based in Dayton, Ohio with the possibility of remote work. Requirements U.S ... Geospatial positioning systems * Experiment scenario metadata * Supporting machine learning feature ...

GIS Analyst

Columbus, OH ยท Remote

$63K - $79K/yr

Familiar with a range of analytical tools for data manipulation, geospatial data modeling, and ... Integrates, coordinates and supports the geographic, cartographic, remote sensing and global ...

Senior Staff / Senior Frontend Engineer

Dayton, OH ยท On-site +1

$111K - $152K/yr

... remote sensing algorithms, tools, and techniques to deliver world-class data exploitation ... Experience developing geospatial or mapping applications, including Cesium * Experience creating or ...

Data Analyst - GEOINT Technical SME

Dayton, OH ยท Remote

$120K - $160K/yr

... more Geospatial Information Systems tools such as ArcView, ArcGIS, Remote View, ArcIMS, ERDAS ... engineering, intelligence, and enterprise information technology markets. SAIC is Redefining ...

Westminster, CO, Dayton, OH, Lake Oswego, OR (onsite), or US-remote Our Department: Corporate Ready ... Lead and grow a cross-functional team including architects, platform and data engineers * Plan and ...

Remote Geospatial Developer information

See Ohio salary details

$59.4K

$73.5K

$87.9K

How much do remote geospatial developer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for remote geospatial developer in Ohio is $73,541.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,900.00 and $78,000.00 per year, depending on experience, location, and employer.

What is a Remote Geospatial Developer job?

A Remote Geospatial Developer is a software developer who specializes in building applications that process, analyze, and visualize geospatial data. They work with Geographic Information Systems (GIS), remote sensing data, and mapping technologies to create solutions across industries such as environmental science, urban planning, and logistics. This role typically involves programming in languages like Python, JavaScript, or SQL, and using tools like QGIS, ArcGIS, and Google Earth Engine. Since the job is remote, developers collaborate with teams and clients virtually using communication and project management tools.

What are some common challenges faced by Remote Geospatial Developers, and how are they typically addressed?

Remote Geospatial Developers often encounter challenges such as managing large spatial datasets, integrating data from multiple sources, and ensuring accuracy in map visualizations. Collaboration across time zones and communicating complex spatial concepts to non-technical stakeholders can also be demanding. To address these issues, teams typically use version control systems, detailed documentation, and regular virtual meetings to stay aligned. Ongoing professional development and staying current with the latest GIS tools further help remote developers tackle technical hurdles efficiently. Effective teamwork and strong project management practices are key to successfully navigating these challenges.

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

To thrive as a Remote Geospatial Developer, you need a solid background in GIS principles, spatial data analysis, and programming languages such as Python or JavaScript, typically supported by a degree in geography, computer science, or a related field. Familiarity with tools like ArcGIS, QGIS, PostGIS, and cloud-based mapping platforms, as well as relevant certifications such as Esri Technical Certifications, is often required. Strong problem-solving skills, self-motivation, and effective remote communication are critical soft skills in this position. These capabilities ensure accurate project delivery, seamless teamwork across distributed teams, and the ability to quickly adapt to evolving geospatial technologies.

What job categories do people searching Remote Geospatial Developer jobs in Ohio look for? The top searched job categories for Remote Geospatial Developer jobs in Ohio are:
What cities in Ohio are hiring for Remote Geospatial Developer jobs? Cities in Ohio with the most Remote Geospatial Developer job openings:
Infographic showing various Remote Geospatial Developer job openings in Ohio as of June 2026, with employment types broken down into 75% Full Time, and 25% Temporary. Highlights an 25% In-person, and 75% Remote job distribution, with an average salary of $73,541 per year, or $35.4 per hour.

Systems Engineer

MMB Solutions LLC

Dayton, OH โ€ข On-site, Remote

Full-time

Posted 21 days ago


Job description

MMB Solutions is seeking a mid-level Systems Engineer to support the design, development, and operation of advanced wireless experimentation infrastructure for the Open 6G Testbed program. The engineer will work on next-generation wireless research involving 5G/6G telemetry architectures, AI-driven network experimentation, spectrum analytics, and integrated sensing and communications (ISAC).

This position will support development of a data architecture and machine learning experimentation platform used to collect, enrich, analyze, and operationalize wireless telemetry data from advanced radio systems operating in research environments.

The Systems Engineer will collaborate with software engineers, RF engineers, and data scientists to build scalable telemetry pipelines, research data infrastructure, and AI-enabled wireless experimentation platforms.

This role is based in Dayton, Ohio with the possibility of remote work.ย ย 

Requirements

U.S. Citizenship

Bachelors' Degree in one of the following:

  • Electrical Engeering
  • Computer Science
  • Systems Engineering
  • Computer Engineering
  • Wireless Communications

Key Responsibilities

Wireless Telemetry Architecture

Design and implement systems that collect and process telemetry data from advanced wireless networks and sensing infrastructure.

Responsibilities include:

  • Designing telemetry collection architectures for 5G and emerging 6G network environments
  • Integrating telemetry from multiple wireless interfaces including:
    • O-RAN E2 interfaces
    • F1 interfaces
    • Core network signaling (N1/N2/N3)
    • RRC signaling and RAN performance metrics
  • Supporting ingestion of telemetry sources such as:
    • User equipment activity
    • Spectrum observations
    • Network performance counters
  • Developing telemetry schemas and system documentation for research datasets.

Wireless Research Data Infrastructure

Support the development of a centralized wireless research data lake used to store and analyze large volumes of telemetry and experimentation data.

Responsibilities include:

  • Designing and supporting scalable data ingestion pipelines
  • Supporting schema enforcement and structured dataset management
  • Developing indexing and query capabilities for telemetry datasets
  • Integrating telemetry sources into research analytics environments
  • Supporting data lifecycle management for wireless experimentation datasets.

Data Enrichment and Machine Learning Integration

Develop and support automated data enrichment pipelines to convert raw telemetry into AI-ready wireless datasets.

Responsibilities include:

  • Implementing automated tagging and labeling pipelines
  • Integrating enrichment sources including:
    • Spectrum monitoring systems
    • Environmental sensors
    • Geospatial positioning systems
    • Experiment scenario metadata
  • Supporting machine learning feature extraction and dataset generation.

Wireless Experimentation Support

Assist in the design and execution of wireless experimentation events within the Open 6G Testbed.

Example experiment areas include:

  • Wireless interference injection scenarios
  • Spectrum sharing experiments
  • Rogue handset detection scenarios
  • Integrated sensing and communications (ISAC) experiments

Responsibilities include:

  • Experiment planning and system integration
  • Dataset generation and collection
  • Experiment documentation and reporting.

AI Model Deployment and Orchestration

Support deployment of an AI model lifecycle management framework integrated with wireless telemetry pipelines.

Responsibilities include:

  • Supporting model versioning and lifecycle management
  • Integrating machine learning models with wireless telemetry systems
  • Deploying distributed inference capabilities across network infrastructure

Supporting AI experimentation using structured wireless datasets.