Embedded Autonomy Engineer

About Mach Industries Founded in 2022, Mach Industries is a rapidly growing defense technology company focused on developing next-generation autonomous defense platforms . At the core of our mission is the commitment to delivering scalable, decentralized defense systems that enhance the strategic capabilities of the United States and its allies. With a workforce of approximately 350 employees , we operate with startup agility and ambition. Our vision is to redefine the future of warfare through cutting-edge manufacturing, innovation at speed, and unwavering focus on national security. We are dedicated to solving the next generation of warfare with lethal systems that deter kinetic conflict and protect global security.

Mach Industries is building an AI-forward autonomy stack for contested environments where GPS and other sensing are unavailable or unreliable. As an Embedded Autonomy Engineer, you own the Linux mission computer that manages cameras, sensors, and the autonomy stack in flight. You bring up Jetson-class compute, integrate high-bandwidth cameras and sensors into Linux, and make perception, planning, decision making, and on-edge inference run in real time under real SWaP, thermal, and vibration constraints. This is a role for an exceptional embedded Linux engineer who wants to work up into the autonomy stack, not just maintain boards: kernel and camera/SerDes bring-up, the sensor-to-GPU pipeline, on-target CUDA/TensorRT runtime, and the autonomy software that sits on top.

Own bring-up and lifecycle of the Linux mission computer: board support packages, device trees, kernel configuration, and bootloaders on NVIDIA Jetson/Tegra and similar SoCs. Integrate high-bandwidth sensors into Linux end to end: MIPI CSI cameras with GMSL/FPD-Link SerDes, V4L2, and ISP tuning, plus radar over PCIe or Ethernet; own time-sync and calibration across the sensor suite. Build and optimize the real-time sensor-to-GPU data path that feeds perception, localization, and inference: zero-copy, DMA, GPU memory management, and camera-to-inference latency. Stand up and maintain the on-target execution environment for autonomy and ML: CUDA/TensorRT runtime, GPU/CPU scheduling, edge containers, and the drivers and libraries the stack depends on. Build and customize the embedded Linux image (Yocto or L4T): kernel, userspace, and reproducible builds for fielded compute. Harden the compute-and-sensing platform for flight: power, thermal, SWaP, vibration, and boot reliability; instrument, reproduce, and root-cause issues on real platforms. Define software-hardware interface specs with electrical engineers during board design cycles; debug integration with logic analyzers, oscilloscopes, and UART. Contribute to the autonomy runtime on the mission computer (middleware, health monitoring, state management) as the engineer who knows the Linux compute layer best.

5+ years of embedded Linux development on custom hardware, with deep expertise in device tree configuration, BSP customization, and kernel bring-up. Camera and sensor integration on Linux: MIPI CSI and V4L2, plus GMSL or FPD-Link SerDes; comfortable owning the sensor-to-memory path. Experience with Yocto or L4T-based build systems; fluency in C, C++, Bash, and Python. Strong hardware debugging with logic analyzers, oscilloscopes, CAN, and UART; reads schematics and collaborates fluently with EEs. Track record taking Linux-based compute platforms from bring-up to real-world deployment, with real-time and performance optimization. Wants to work up the stack into autonomy and on-target inference, not only maintain the OS and boards.

NVIDIA Jetson and the L4T stack; CUDA, TensorRT, GStreamer/DeepStream for on-target inference and media pipelines. ROS 2/copper-rs/dora-rs and integration of autonomy, perception, or localization software on the mission computer. Multi-sensor time-sync and calibration (PTP, hardware