Embedded Firmware Engineer - AI Edge Systems
We are looking for an Embedded Firmware Engineer specializing in AI Edge Computing to design and build the low-level intelligence that powers next-generation advanced autonomous robots. You will work at the intersection of embedded systems, real-time software, AI acceleration, and robotics hardware, transforming algorithms into reliable, production-ready edge intelligence.
At LeonLegion, we don’t just write firmware - we engineer cognition at the edge.
REQUIREMENTS:
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Bachelor’s or Master’s degree in Embedded Systems, Computer Engineering, Electronics, or Computer Science.
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Strong proficiency in C/C++ for embedded systems.
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Solid experience with Embedded Linux and/or RTOS.
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Understanding of AI edge deployment constraints (latency, power, thermal, memory).
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Experience with cross-compilation, toolchains, and debugging tools (GDB, JTAG, logic analyzers).
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Familiarity with communication protocols: CAN, Ethernet, UART, SPI, I2C.
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Experience in robotics, automotive, or industrial embedded systems (≥ 4 years preferred).
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Strong problem-solving mindset and attention to engineering detail.
RESPONSIBILITIES
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Design, develop, and optimize embedded firmware/software for AI edge platforms (MCU, NPU, SoC, SoM, FPGA-based systems).
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Implement real-time and near-real-time software for perception, control, and decision-making pipelines.
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Integrate and optimize AI inference engines (TensorRT, ONNX Runtime, TFLite, custom accelerators).
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Work with Linux Embedded / RTOS environments (Yocto, Buildroot, FreeRTOS, Zephyr).
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Develop device drivers, BSPs, bootloaders, and low-level system services.
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Optimize performance, latency, power consumption, and memory footprint.
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Interface with sensors, actuators, and peripherals (CAN, UART, SPI, I2C, Ethernet).
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Collaborate closely with AI, robotics, electronics, and mechanical teams.
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Support system bring-up, debugging, validation, and field testing.
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Produce clean, maintainable documentation following professional engineering standards.
Nice to Have
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Experience with NPU / GPU / FPGA acceleration.
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Knowledge of Yocto Project, BSP customization, and kernel configuration.
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Experience with ROS / ROS 2 integration at the embedded level.
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Understanding of functional safety and secure boot.
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Exposure to motion control, sensor fusion, or real-time perception systems.