Senior Engineer, Lab automation

Lab Infrastructure & Device Uptime

• Own end-to-end lab operations across multiple hardware boards and product lines, with proactive monitoring of device health, thermals, logs, and connectivity.
• Manage power infrastructure (PDUs, adapters, backups) and perform board-level debugging and hardware rework (soldering, wiring, component replacement) using multimeters, oscilloscopes, and logic analyzers.
• Handle firmware flashing, device recovery, and boot/log-level debugging on Linux and MCU systems.
• Maintain device inventory, documentation, and infrastructure readiness for QA and Firmware teams.

Simulation, Automation & Innovation

• Design and build simulation setups that replicate real-world field scenarios for MVAI-enabled drivecams, translating device behavior into reproducible, automated lab test environments.
• Develop Python/Bash scripts and test automation software for device monitoring, log collection, and hardware-in-the-loop (HIL) workflows.
• Integrate hardware lab setups with CI/CD pipelines (Jenkins, GitLab CI) and contribute to automation frameworks.
• Support IoT, camera, and telemetry device setups with reliable MQTT-based communication between devices and backend systems.
• Configure and troubleshoot networking (IP allocation, routing, switching) to ensure stable multi-device connectivity.

What You'll Need:

• Minimum 6  years of combined experience in hardware lab management, embedded device validation, and test automation.
• Strong expertise in board-level debugging, soldering/rework, power architecture, and hardware root cause analysis.
• Extensive experience with embedded Linux and MCU systems — firmware flashing, bootloader/debug log analysis, device recovery.
• Proficiency in Python and/or Bash scripting for automation and tooling.
• Experience integrating hardware labs with CI/CD pipelines and automated test frameworks.
• Excellent communication and analytical skills with the ability to mentor others and work with global teams

Good to Have (the more, the better):

• Hands-on experience with simulation or emulation environments for camera, ADAS, or telematics devices.
• Familiarity with MVAI pipelines, computer vision model validation, or sensor data replay.
• Deep understanding of MQTT and IoT communication architecture for camera/telematics systems.
  • Strong networking fundamentals (TCP/IP, routing, switching, DHCP).