The Role

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.

Key Responsibilities

• 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.

Required Qualifications

• 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.

Preferred Qualifications

• 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 triggering)
• GPU pipeline and memory optimization, DMA, and zero-copy under real-time constraints.
• Nix or NixOS workflows; strong opinions about Rust.
• Experience in contested or degraded environments (RF denial, low-light/night, high-vibration platforms).

Disclosures

This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license.

The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offers may vary based on (but not limited to) work experience, education and training, critical skills, and business considerations. Highly competitive equity grants are included in most offers and are considered part of Mach's total compensation package. Mach offers benefits such as health insurance, retirement plans, and opportunities for professional development.

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