Embedded Autonomy Engineer: Linux Flight Compute

Mach Industries; Huntington Beach (CA); On-site; USD 140,000 - 210,000; Full time

Benefits offered by this job

Health insurance

Retirement plans

Equity grants

Professional development

Job summary

Mach Industries is building an AI-forward autonomy stack for contested environments. As an Embedded Autonomy Engineer, you own the Linux mission computer, bring up kernel and device trees on NVIDIA Jetson/Tegra, and integrate high-bandwidth sensors into Linux end-to-end.

You will optimize the sensor-to-GPU path for real-time perception and work up into autonomy and on-target inference with CUDA/TensorRT runtimes.

Qualifications

• 5+ years of embedded Linux development on custom hardware with kernel bring-up and device-tree configuration.

Responsibilities

• Own bring-up and lifecycle of the Linux mission computer: BSPs, device trees, kernel config, bootloaders on NVIDIA Jetson/Tegra.
• Integrate high-bandwidth sensors into Linux end-to-end: MIPI CSI cameras, GMSL/FPD-Link SerDes, V4L2, ISP tuning, sensor synchronization.
• Build and optimize the real-time sensor-to-GPU data path for perception/localization/inference: zero-copy, DMA, GPU memory management.
• Maintain the on-target execution environment for autonomy and ML: CUDA/TensorRT runtime, edge containers, drivers/libraries.
• Build and customize the embedded Linux image (Yocto or L4T): kernel, userspace, reproducible builds.
• Harden the compute-and-sensing platform for flight: power, thermal, SWaP, vibration; debug and root-cause issues on real platforms.
• Define software-hardware interface specs with engineers; debug with logic analyzers and scopes.
• Contribute to autonomy runtime on the mission computer (middleware, health monitoring, state management).

Skills

Embedded Linux

Kernel bring-up

Device tree

Camera integration

C/C++

Python

Jetson/NVIDIA

Tools

Yocto

L4T

CUDA

TensorRT

GStreamer

Jetson

Job description

Mach Industries is building an AI-forward autonomy stack for contested environments. As an Embedded Autonomy Engineer, you own the Linux mission computer, bring up kernel and device trees on NVIDIA Jetson/Tegra, and integrate high-bandwidth sensors into Linux end-to-end.

You will optimize the sensor-to-GPU path for real-time perception and work up into autonomy and on-target inference with CUDA/TensorRT runtimes.