Embedded Systems Engineer

Work schedule: Hybrid-two days onsite each week
Short Summary


This Systems Engineer will integrate electrical hardware, embedded computers, C++ and Python software, cameras, sensors, networking, and AI into operational railroad systems. The person will troubleshoot issues across the entire technology stack, collaborate with multiple engineering teams, and deploy and test equipment in laboratories and railroad field environments.

Position Summary


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


This role requires a systems-level understanding of how hardware, software, data, AI, networking, and field equipment work together. The Systems Engineer will collaborate with engineering, data science, architecture, cybersecurity, DevSecOps, and field teams to deliver reliable solutions for machine vision, trackside inspection, autonomous platforms, robotics, drones, and AI-enabled monitoring.


Key Responsibilities

Systems Design and Integration

• Translate operational needs into system architectures, requirements, 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 challenges.
• Troubleshoot issues involving hardware, firmware, software, networking, sensors, AI, data quality, and field conditions.
• Collaborate with Solution Architects, Software Engineers, Data Scientists, Electrical Engineers, cybersecurity teams, DevSecOps, field personnel, and other Systems Engineers.

Embedded Systems, Software, and AI

• Configure, integrate, and troubleshoot embedded computing systems and hardware/software interfaces.
• Develop and maintain C++ and Python software, scripts, and tools.
• Support device control, data acquisition, communications, diagnostics, testing, configuration, deployment, and monitoring.
• Integrate machine learning and computer vision models into operational systems.
• Ensure sensor and image data are captured, processed, and delivered reliably.
• Analyze system performance to identify integration problems and bottlenecks.
• Determine whether field issues originate from sensors, data quality, AI models, software, hardware, networking, or system integration.

Electrical, Vision, and Network Infrastructure

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

Field Deployment and Railroad Applications

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

Example Systems


Projects may include:

• Trackside machine-vision systems
• Camera-based inspection
• AI-enabled defect and object classification
• Railcar identification and tracking
• Autonomous or semi-autonomous robots
• Drone inspection systems
• Distributed camera and sensor networks
• Edge-computing platforms
• Custom PCB-based systems

Required Qualifications

• Bachelor's degree in Electrical Engineering, Computer Engineering, Mechanical Engineering, Aerospace Engineering, Robotics, Mechatronics, 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 hardware, software, embedded computers, networks, sensors, and field equipment.
• Understanding of electrical and electronic fundamentals, including sensors, signals, power, digital and analog I/O, embedded systems, and components.
• Ability to read schematics, technical drawings, datasheets, and system documentation.
• Understanding of computer networking, 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, hardware development, microcontrollers, embedded processors, embedded Linux, or edge-computing platforms.
• 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 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 across related areas to integrate and support a complete system. Candidates do not need to be experts in every technology.


The successful candidate will be a hands-on systems thinker who can:

• Work across electronics, embedded software, networking, sensors, machine vision, AI, robotics, and field engineering.
• Diagnose problems that cross traditional engineering boundaries.
• Work effectively in ambiguous, real-world environments.
• Take ownership of the complete solution and ensure reliable field performance.