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Project Canary (via its subsidiary Aeris Technologies) develops laser-based gas analyzers for trace gas monitoring in environmental, industrial, laboratory, and field applications. The company combines high-fidelity sensors, multi-source data, and proprietary analytics to help energy companies measure and reduce their emissions footprint.
The Embedded Test Automation Engineer will design and maintain the automated production test environment for embedded Linux instruments. This role bridges hardware, embedded software, lab systems, and cloud infrastructure to enable reliable device provisioning, calibration, testing, and recovery.
Key responsibilities include:
- Build and maintain an integrated automated test environment for embedded Linux hardware
- Automate device identification, network booting, disk partitioning, file system configuration, and software installation
- Develop secure workflows that store and retrieve device-specific calibration results and instrument configuration data from cloud-based systems
- Design and expand automated test suites using Python, Pytest, LabVIEW, or similar tools
- Develop Python tools that integrate with existing LabVIEW and Python calibration systems
- Troubleshoot issues across hardware, operating systems, software, and network connections
- Partner with hardware, firmware, test, manufacturing, and cloud teams to improve device bring-up, testing, and configuration
- Improve the reliability, repeatability, and maintainability of production test processes
This role requires solving problems across hardware and software domains and turning complex production processes into reliable, repeatable automation.
REQUIREMENTS:
- 4–7 years of experience in embedded systems, test automation, manufacturing test engineering, or a related field
- Strong Python programming skills and experience building maintainable automation tools
- Hands-on experience using Pytest or a similar framework for hardware, system, or integration testing
- Working knowledge of embedded Linux, including boot processes, network booting, storage partitioning, and file system configuration
- Experience integrating systems through APIs, cloud databases, or other data services
- Ability to diagnose complex issues across hardware, operating systems, software, and networks
- Experience working across engineering disciplines to deliver production-ready systems
- Practical approach to documentation, error handling, and long-term maintainability
Nice to have: LabVIEW automation and Python integration experience; hardware-in-the-loop test environments; CI/CD practices for embedded systems; production provisioning or manufacturing test systems; cloud-based data storage and device configuration management.
