Systems Integration Engineer

Aptonet; Atlanta (GA); On-site; USD 90,000 - 130,000; Full time

Job summary

Aptonet is seeking a hands-on Systems Engineer to design, build, and support technology solutions for railroad environments in the United States. You will integrate electrical hardware, embedded computers, software, cameras, sensors, networking, machine learning models, and field infrastructure into dependable operational systems.

The role spans hardware, software, data science, cybersecurity, DevSecOps, and field operations, requiring broad system understanding and practical problem solving

Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Mechatronics, or equivalent relevant experience.

Responsibilities

• Translate operational needs into system requirements, architectures, interfaces, implementation plans, and integration strategies.
• Integrate electrical, mechanical, embedded, software, networking, sensing, AI, and field infrastructure components.
• Connect custom electronics, PCBs, embedded computers, cameras, sensors, networking equipment, servers, software, and AI models.
• Identify technical risks, dependencies, performance limitations, and integration issues.
• Troubleshoot problems involving hardware, firmware, software, networks, sensors, AI models, data quality, and field conditions.
• Collaborate with engineering, data science, architecture, cybersecurity, DevSecOps, and field operations teams.

Skills

C++

Python

Embedded systems

Networking

Computer vision

Machine learning

System integration

Diagnostics

Education

Bachelor's degree in Electrical Engineering, Computer Engineering, Mechatronics, or equivalent

Tools

Docker

Git

Linux

Embedded Linux

PCB design

Job description

We are seeking a hands-on Systems Engineer to build and support technology solutions for railroad environments. This role is responsible for integrating electrical hardware, embedded computers, software, cameras, sensors, networking, machine learning models, servers, and field infrastructure into dependable operational systems.

The Systems Engineer will work across hardware, software, data science, solution architecture, cybersecurity, DevSecOps, and field operations. The position requires a broad understanding of how individual components interact and the ability to diagnose problems across the complete system.

Key Responsibilities

System Design and Integration

• Translate operational needs into system requirements, architectures, interfaces, implementation plans, and integration strategies.
• Integrate electrical, mechanical, embedded, software, networking, sensing, AI, and field infrastructure components.
• Connect custom electronics, PCBs, embedded computers, cameras, sensors, networking equipment, servers, software, and AI models.
• Identify technical risks, dependencies, performance limitations, and integration issues.
• Troubleshoot problems involving hardware, firmware, software, networks, sensors, AI models, data quality, and field conditions.
• Collaborate with engineering, data science, architecture, cybersecurity, DevSecOps, and field operations teams.

Embedded Software and AI

• Configure and troubleshoot embedded computing systems and hardware/software interfaces.
• Develop and maintain C++ and Python applications, scripts, and tools.
• Support device control, data acquisition, communications, diagnostics, testing, configuration, deployment, and monitoring.
• Integrate computer vision and machine learning models into operational systems.
• Ensure sensor and image data are captured, processed, and delivered reliably.
• Analyze system behavior to identify bottlenecks and determine the source of performance problems.

Electrical, Vision, and Network Infrastructure

• Design and support field-deployed electrical and electronic systems, including power supplies, sensors, communications equipment, embedded computers, and PCBs.
• Read schematics, PCB documentation, datasheets, specifications, and technical drawings.
• Select components based on electrical, environmental, performance, and operational requirements.
• Integrate cameras, lenses, lighting, optics, image-acquisition systems, and sensors for inspection and machine-vision applications.
• Evaluate camera positioning, field of view, resolution, exposure, lighting, image quality, environmental effects, and data suitability.
• Configure and troubleshoot servers, switches, routers, wireless equipment, IP networks, edge platforms, databases, cloud interfaces, and enterprise infrastructure connections.
• Develop reliable solutions for environments affected by weather, vibration, temperature, lighting, and limited connectivity.

Field Deployment

• Install, commission, validate, test, and troubleshoot systems in laboratories, rail yards, maintenance facilities, test-track environments, and trackside locations.
• Use logs, sensor data, images, diagnostics, and operational information to evaluate performance and isolate failures.
• Develop tools and procedures for installation, configuration, testing, deployment, maintenance, and troubleshooting.
• Support railroad applications involving track inspection, rolling-stock inspection, railcar identification and tracking, automated monitoring, safety, maintenance, and rail-yard operations.
• Travel to field locations as needed.

Example Projects

• Camera-based inspection systems
• AI-enabled defect and object classification
• Railcar identification and tracking
• Autonomous or semi-autonomous robots
• Distributed camera and sensor networks

Required Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Mechatronics, a related engineering discipline, or equivalent relevant experience.
• Experience developing, integrating, or troubleshooting complex hardware/software systems.
• Working knowledge of C++ and Python.
• Experience troubleshooting hardware, software, embedded computers, networks, sensors, and field equipment.
• Understanding of sensors, signals, power, electrical components, digital and analog I/O, and embedded systems.
• Ability to read schematics, technical drawings, datasheets, and system documentation.
• Understanding of IP networking and networked devices.
• Strong analytical, communication, collaboration, and hands-on problem-solving skills.
• Ability to work across engineering disciplines and learn new technologies.

Preferred Qualifications

• Experience with robotics, mechatronics, autonomous systems, drones, industrial automation, motion systems, or physical system integration.
• Experience with computer vision, machine learning, cameras, optics, lighting, image acquisition, sensor fusion, localization, tracking, or perception systems.
• Experience with PCB design, electronics, wiring, microcontrollers, embedded processors, embedded Linux, or edge-computing platforms.
• Experience with Linux servers, industrial networks, communications protocols, SQL, databases, Docker, containers, virtualization, Git, CI/CD, DevSecOps, real-time systems, or high-performance computing.
• Experience supporting systems in outdoor, industrial, transportation, railroad, or other demanding physical environments.

Ideal Candidate

The ideal candidate has deep expertise in at least one engineering discipline and enough knowledge of adjacent areas to integrate an entire system. They do not need to be an expert in every technology.

Successful candidates will be hands-on systems thinkers who can:

• Work across electrical hardware, embedded software, networking, sensing, computer vision, AI, robotics, and field engineering.
• Investigate problems that cross traditional engineering boundaries.
• Operate effectively in ambiguous, real-world environments.
• Take ownership of the complete solution and ensure it performs reliably.