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Remote Autonomous Systems Engineer Jobs in Ohio (NOW HIRING)

MMB Solutions LLC

Systems Engineer

Dayton, OH · On-site +1

This role is based in Dayton, Ohio with the possibility of remote work. Requirements U.S ... Computer Science * Systems Engineering * Computer Engineering * Wireless Communications Key ...

US Bank

Nexthink Systems Engineer

Cincinnati, OH · Remote

The Nexthink Systems Engineer directs or recommends enhancements for system performance ... Remote Actions * Dashboards & Investigations * Campaigns & Alerts * Application Experience ...

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Remote Autonomous Systems Engineer information

What are the key skills and qualifications needed to thrive as a Remote Autonomous Systems Engineer, and why are they important?

To thrive as a Remote Autonomous Systems Engineer, you need a strong background in robotics, control systems, programming (such as Python or C++), and a relevant engineering degree. Experience with simulation tools like ROS (Robot Operating System), MATLAB, and familiarity with machine learning or AI frameworks are typically required, along with certifications in automation or robotics being advantageous. Strong problem-solving skills, self-motivation, and effective remote communication set top candidates apart in this role. These skills and qualities are essential for designing, troubleshooting, and improving autonomous systems while collaborating efficiently within distributed teams.

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

Remote Autonomous Systems Engineers often encounter challenges related to communication and collaboration, as they work with multidisciplinary teams across different locations and time zones. Managing system integration and troubleshooting without on-site access can also pose difficulties, requiring strong documentation and remote diagnostic tools. Staying updated on rapidly evolving technologies in autonomy further demands ongoing learning. To address these challenges, engineers should leverage clear communication channels, utilize collaborative platforms, and participate in continuous training opportunities.

What are Remote Autonomous Systems Engineers?

Remote Autonomous Systems Engineers are professionals who design, develop, and maintain autonomous systems—such as drones, robots, or vehicles—while working remotely. They use advanced software, sensors, and algorithms to ensure these systems can operate independently and safely. Their work involves tasks like programming control systems, integrating hardware components, and troubleshooting issues from a remote location. These engineers often collaborate with teams virtually and leverage cloud-based tools to monitor and update autonomous systems deployed in various environments.
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Remote Autonomous Systems Engineer jobs near you

Systems Engineer

MMB Solutions LLC

Dayton, OH • On-site, Remote

Full-time

Posted 26 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.  

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.

Apply