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Salary
≈ $105k – $206k per year (Estimated)
Location
Hybrid (Atlanta, United States)
Seniority
Middle · 3+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Sep 8, 2026. AeroVect scores B on the Alion truth index.

Overview
Company
Impact
Profile match
AeroVect is an autonomous driving technology company founded in 2020 that develops the AeroVect Driver, a self-driving software and sensor kit that automates airport ground support equipment such as baggage tractors and cargo haulers. Its systems are deployed with airlines and ground handlers at passenger and cargo hubs, and it hires motion planning and localization engineers, operations safety leads and autonomous vehicle test drivers in Atlanta, Toronto and New York. The company is headquartered in South San Francisco, California, United States.

Who We Are

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

As a Platform Engineer at AeroVect, you will own the reliability, performance, and scalability of the software foundation that powers our autonomous ground vehicle fleet. You will be responsible for managing and optimizing our Ubuntu-based operating system images, middleware, and device drivers that interface with a diverse multi-sensor ROS 2 stack. Your work enables our perception and autonomy teams to iterate rapidly and deliver safe, production-ready capabilities to customers worldwide.

You Will

  • Design, build, and maintain custom Ubuntu/Linux distributions tailored for real-time, safety-critical autonomous vehicle workloads.

  • Optimize and tune ROS 2 DDS middleware (e.g., Cyclone DDS, Fast DDS) for low-latency, high-throughput multi-sensor data flows.

  • Develop, integrate, and maintain kernel modules and user-space drivers for LiDARs, cameras, radars, GNSS/INS, CAN, and other vehicle interfaces.

  • Maintain and expand the network interfaces of the system.

  • Implement observability and logging solutions to monitor system health, performance, and resource utilization in both lab and field deployments.

  • Collaborate with autonomy, perception, and controls engineers to profile CPU/GPU usage and remove bottlenecks across the stack.

  • Harden the platform for production by applying security patches, enforcing secure boot, and implementing over-the-air (OTA) update pipelines.

  • Own CI/CD pipelines for OS images and driver packages; automate build, test, and deployment processes.

  • Provide on-call support for platform components during field trials and customer pilots.

  • Contribute to technical documentation and best-practice guidelines for internal and external developers.

You Have

  • 3+ years of experience developing or maintaining Linux-based embedded or robotics platforms.

  • Deep knowledge of Ubuntu or Linux systems, including package management, systemd, networking, and kernel configuration.

  • Proficiency in C/C++ and Python; experience writing or debugging kernel modules and user-space drivers.

  • Hands-on experience with ROS 1 or ROS 2 in a production or research setting.

  • Familiarity with common communication buses and protocols (USB, Ethernet, CAN, PCIe, SPI, I2C).

  • Strong grasp of real-time performance tuning, profiling tools (perf, eBPF, tracing), and resource-constrained optimization.

  • Experience with Git, Docker/OCI containers, and automated build systems (Yocto, Buildroot, or similar).

We Prefer

  • Prior work on autonomous vehicles, drones, or other safety-critical robotic systems.

  • Experience with ptp4l configurations in complex systems.

  • Experience with v4l2/gstreamer.

  • Experience with Nvidia Orin/Jetson platforms.

  • Experience customizing the Linux kernel for PREEMPT_RT or other real-time patches.

  • Knowledge of DDS internals and QoS tuning for deterministic data delivery.

  • Familiarity with GPU acceleration frameworks (CUDA, Vulkan) and heterogeneous compute scheduling.

  • Experience integrating functional safety libraries and tools (e.g., MISRA, ISO 26262 compliance workflow).

  • Comfort working in a fast-paced startup environment and supporting field deployments at airports or other industrial sites.

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