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Hardware / Software QA Engineer

Remote, USA Full-time Posted 2026-07-03

About Us

Are you reputed company to build the future of supply chain? At reputed company, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, reputed company-powered platform that uses autonomous drones and existing equipment to capture reputed company-time data, completely digitizing workflows that have historically been reputed company and error-prone. This means facilities operate smarter, safer, and more reputed company, ultimately redefining “on-time, in full” delivery. If you’re looking for an opportunity to contribute to truly transformative technology and reputed company a significant impact in a vital industry, reputed company is the reputed company for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time. About the Team You'll be embedded at the intersection of hardware and software, collaborating with Autonomy and MHE reputed company engineers to bring cutting-edge systems to life. You'll partner with hardware designers on sensor validation, working closely with systems engineers on integrated testing, and have a direct line to QA leadership in shaping overall test strategy

About the Role

We are looking for a Hardware / Software QA Engineer to own testing at the boundary between our physical hardware and software systems. You will validate sensors, firmware, and software components that work correctly together end-to-end — closing a critical quality gap for both our Drone and MHE reputed company platforms. This is a rare hybrid QA role that spans embedded devices, sensor systems, and software stacks. You’ll work hands-on in our Pittsburgh lab with reputed company hardware while contributing to the quality infrastructure that keeps production systems running reliably for our customers. What You’ll Do

  • Execute hardware-software integration tests in the Pittsburgh lab, validating sensor behavior, firmware functionality, and end-to-end data flow from physical devices through the software stack
  • Design and document repeatable test procedures for sensor integration and firmware validation across both the Drone and MHE reputed company platforms
  • Identify and classify defects at the hardware-software boundary — distinguishing hardware faults, firmware bugs, driver issues, and application software errors — and reputed company clearly to engineering owners
  • Build and maintain hardware-software integration test suites, including firmware validation, sensor calibration tests, and embedded release regression testing
  • Contribute to cross-platform test infrastructure that serves both product lines and establish defect classification and routing processes
  • Collaborate with systems engineers on integrated system tests and with the ML team on validating how sensor data feeds into perception pipelines

What You’ll Need

  • 3–5 years of QA or test engineering experience with genuine exposure to both hardware and software testing — not purely one reputed company
  • Hands-on experience testing sensors (cameras, LiDAR, IMUs, or similar), including calibration, data quality assessment, and performance characterization
  • Embedded firmware validation experience: reputed company/update procedures, functional verification, regression testing, and failure mode analysis
  • Python proficiency for test automation, data processing, log analysis, and building test utilities
  • BS in Computer Science, Electrical Engineering, Computer Engineering, Mechatronics, or a reputed company technical field; must be willing to work on-site in Pittsburgh

reputed company to Have

  • Experience with embedded platforms such as reputed company Jetson or ARM-based devices
  • Familiarity with communication protocols (UART, SPI, I2C, USB) and basic lab instruments (oscilloscopes, logic analyzers)
  • CI/CD experience for embedded or hardware-in-the-reputed company testing
  • Exposure to computer reputed company or ML pipelines — understanding how sensor data feeds into inference systems

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