About this role
ABOUT US Aeris Technologies, Inc., a subsidiary of Project Canary, develops and commercializes advanced, laser-based gas analyzers for trace gas monitoring across environmental, industrial, laboratory, and field applications. Aeris instruments deliver high-precision, real-time measurements of greenhouse gases, atmospheric pollutants, and natural gas leak indicators, helping customers collect reliable data in fixed, mobile, handheld, and aerial configurations. As part of Project Canary, Aeris supports a broader climate technology platform that helps energy companies improve and report on their emissions footprint. Project Canary combines high-fidelity sensors, data from multiple technologies and sources, and proprietary analytics to deliver actionable insights that help operators stop leaks faster, reduce risk, streamline reporting, and differentiate their operations for key stakeholders. Aeris’s technology brings lab-grade gas sensing performance into the field, supporting applications in environmental monitoring, industrial safety, air quality, research, and emissions measurement. About the Role The Embedded Test Automation Engineer will build and maintain the automated production test environment for our embedded Linux instruments. This role connects hardware, embedded software, lab systems, and cloud infrastructure to support reliable device provisioning, calibration, testing, and recovery. You will develop tools and workflows that identify and network-boot devices, configure storage and file systems, install software, and validate system functionality. You will also integrate device calibration results and configuration parameters with cloud-based systems to maintain accurate production records and support disaster recovery. We’re looking for an engineer who enjoys solving problems across hardware and software and can turn complex production processes into reliable, repeatable automation. 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.