Senior Computer Vision Engineer Jobs in Marietta, GA

Systems Engineer

Overview

We are seeking a hands-on Systems Engineer to design, integrate, deploy, and support complex technology systems used in railroad environments. These solutions combine electrical hardware, embedded computing, software, cameras, sensors, networking, machine learning, servers, and physical infrastructure.

This role works across hardware, software, data science, solution architecture, and field operations to ensure complete systems operate reliably in real-world environments. Applications may include machine vision, trackside inspection, railcar identification, autonomous platforms, robotics, drones, distributed sensing, and AI-enabled monitoring.

The ideal candidate has depth in at least one engineering discipline and the ability to work broadly across electrical/electronic systems, embedded software, networking, sensing, vision, AI, robotics, and field engineering.

Key Responsibilities

• Design and integrate complete systems spanning electrical, embedded, software, networking, sensing, AI, and field infrastructure.
• Translate operational requirements into system architectures, interfaces, implementation plans, and integration strategies.
• Integrate and troubleshoot electronics, PCBs, embedded computers, cameras, sensors, networking equipment, servers, software, and AI models.
• Write and maintain C++ and Python software, scripts, and tools for device control, data acquisition, communications, diagnostics, testing, configuration, deployment, and monitoring.
• Diagnose system issues across hardware, firmware, software, networking, sensors, data quality, AI/model performance, and environmental conditions.
• Configure and troubleshoot embedded computing platforms and hardware/software interfaces.
• Integrate machine learning and computer vision solutions and ensure reliable capture, processing, and delivery of sensor and image data.
• Read schematics, PCB documentation, datasheets, technical drawings, and specifications and support component selection and hardware integration.
• Integrate cameras, lenses, lighting, optics, sensors, and image-acquisition systems for machine vision and inspection applications.
• Evaluate camera placement, field of view, resolution, exposure, lighting, image quality, and environmental effects.
• Configure and troubleshoot servers, switches, routers, wireless equipment, edge platforms, IP networks, databases, cloud interfaces, and enterprise infrastructure connections.
• Deploy, commission, validate, test, and troubleshoot systems in laboratories, test-track environments, rail yards, trackside locations, maintenance facilities, and other field settings.
• Analyze logs, operational data, sensor information, images, and diagnostics to evaluate performance and isolate failures.
• Develop tools and procedures that simplify system installation, configuration, testing, maintenance, and troubleshooting.
• Collaborate with Software Engineers, Data Scientists, Electrical Engineers, Solution Architects, IT/cybersecurity, DevSecOps, field personnel, and other engineering teams.
• Travel to field locations as needed.

Required Qualifications

• Bachelor’s degree in Electrical Engineering, Computer Engineering, Mechatronics, or a related engineering discipline, or equivalent relevant experience.
• Experience developing, integrating, or troubleshooting complex hardware/software systems.
• Working knowledge of C++ and Python.
• Ability to troubleshoot systems involving hardware, software, embedded computing, networking, sensors, and field equipment.
• Understanding of electrical and electronic fundamentals, including sensors, signals, power, digital/analog I/O, embedded systems, and electronic components.
• Ability to read schematics, technical drawings, datasheets, and system documentation.
• Understanding of computer networking fundamentals, including TCP/IP, IP networking, and networked devices.
• Strong analytical and hands-on problem-solving skills in laboratory and field environments.
• Strong communication and collaboration skills with the ability to work across multiple engineering disciplines.
• Ability to learn new technologies and take ownership of complete system performance.

Preferred Qualifications

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

Candidate Profile

Successful Systems Engineers are hands-on systems thinkers who can understand how electronics, computers, networks, software, cameras, sensors, AI models, and physical equipment work together as one operational system.

Candidates do not need to be experts in every discipline. Strong technical fundamentals, practical troubleshooting ability, adaptability, curiosity, and the willingness to learn across engineering domains are essential.