ROS / ROS2 Developer — Python-Based Edge Robotics
Buget: $20.0 - $30.0
HOURLY / FULL_TIME
⭐ 4.98 (55)
United States
embedded-applications, device-firmware, embedded-linux, python, docker, robotics
This is a hands-on engineering role focused on building reliable ROS / ROS2 systems in Python for production edge devices. You will work on device control, sensor coordination, motor control, camera pipelines, safety logic, node communication, health monitoring, and deployment reliability.
The ideal candidate is comfortable writing clean Python code for real hardware, debugging ROS nodes in the field, and making robotics systems stable enough for hospital environments.
Responsibilities
* Develop, maintain, and improve ROS / ROS2 nodes using Python.
* Build reliable communication between cameras, sensors, motors, lights, AI models, and cloud-connected services.
* Work on device logic for human detection, room activity, UV safety, sensor status, motor movement, and real-time state coordination.
* Implement ROS topics, services, actions, parameters, launch files, timers, and lifecycle behavior.
* Debug and improve node stability, timing, message flow, resource usage, and failure recovery.
* Integrate hardware components such as cameras, GPIO-controlled devices, motors, lights, relays, and sensors.
* Work with edge devices such as NVIDIA Jetson and Linux-based embedded systems.
* Build diagnostics and health checks for ROS nodes, hardware status, camera availability, sensor status, and system readiness.
* Improve logging, monitoring, restart logic, and fault recovery for production devices.
* Collaborate with computer vision, edge AI, cloud, hardware, and QA teams.
* Support field debugging and help analyze device behavior from logs, telemetry, and system state.
* Package and deploy ROS-based services using Docker or similar deployment workflows.
What We’re Looking For
* Strong Python programming experience.
* Hands-on experience with ROS or ROS2, preferably ROS2.
* Experience building real robotics or edge-device systems, not only simulations.
* Strong understanding of ROS nodes, topics, services, actions, parameters, launch files, and message types.
* Comfortable working with Linux, shell commands, system services, logs, and device-level debugging.
* Experience integrating hardware components such as cameras, sensors, motors, GPIO, serial devices, or microcontrollers.
* Ability to write robust, maintainable code for long-running production systems.
* Strong debugging skills across software, hardware, networking, and runtime issues.
* Understanding of real-time or near-real-time system behavior, timing, state machines, and failure handling.
* Ability to work independently in a fast-moving startup environment.
Nice to Have
* Experience with NVIDIA Jetson devices.
* Experience with Docker-based deployment for edge devices.
* Experience with camera pipelines, OpenCV, GStreamer, CSI/USB cameras, or video streaming.
* Experience with GPIO, I2C, UART, serial communication, relays, motors, or embedded control.
* Experience with ROS2 lifecycle nodes, diagnostics, launch systems, and multi-node orchestration.
* Experience with MQTT, cloud-connected IoT devices, OTA updates, telemetry, or fleet monitoring.
* Experience with robotics safety logic, human detection, or safety-critical automation.
* Experience working with computer vision models running on edge devices.
* Experience debugging field devices remotely.
Ideal Candidate
The ideal candidate is a practical robotics software engineer who can make ROS systems work reliably on real devices. You should be comfortable moving between Python code, ROS architecture, Linux debugging, hardware integration, and production reliability.
You should care about clean architecture, but also be willing to debug messy real-world issues such as camera failures, node crashes, timing problems, hardware disconnects, resource limits, and inconsistent field behavior.
Example Projects
* Build ROS2 nodes to coordinate camera input, AI inference, motor movement, and safety logic.
* Create a device state machine for room monitoring, human detection, UV readiness, and interruption handling.
* Improve restart and recovery logic when a camera, sensor, or ROS node fails.
* Build health-check nodes that report device status, node status, hardware status, and runtime errors.
* Integrate GPIO-controlled lights, motors, sensors, and relays into the ROS system.
* Improve launch files, configuration management, and deployment flow for multiple device versions.
* Debug production logs from deployed hospital devices and identify root causes.
* Package ROS services inside Docker for reliable deployment on NVIDIA Jetson.
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