Embedded Systems Engineer

About Neural Earth

Neural Earth brings clarity to risk, helping decision makers act with confidence and enact resilient business critical decisions. Today’s environmental, economic, and infrastructure challenges are deeply interconnected yet the information required to understand these relationships are scattered across siloed and aging systems. As risk evolves, organizations go extinct when reliant on incomplete or outdated information. Neural Earth unifies our planet's data and deploys a single AI powered system, enabling revenue-driving decisions in seconds, not weeks.

About the position

Neural Earth is seeking an Embedded Systems Engineer to design, integrate, and deploy flight control and autonomy software for next-gen unmanned aerial systems (UAS). You’ll work on everything from real-time firmware to mission autonomy stacks supporting swarm coordination, adaptive routing, and multi-agent decision systems.

This is a highly technical role requiring deep knowledge of embedded architectures, real-time operating systems (RTOS), sensor integration, and low-level control for robotics.

Responsibilities

  • Develop firmware and embedded software for custom and open-source flight controllers (e.g., PX4, ArduPilot).
  • Integrate GNSS, IMUs, Lidar, Radar, magnometer, and multispectral sensors.
  • Familiarity with GPS. GLONASS a plusEnable autonomous navigation and flight control.
  • Optimize onboard systems for size, weight, power, and thermal efficiency.
  • Collaborate with autonomy and AI teams on sensor fusion and path planning.
  • Conduct system-in-the-loop (SIL) and hardware-in-the-loop (HIL) tests.
  • Contribute to onboard autonomy, telemetry, and failsafe behaviors.

Qualification

  • 3-5+ years of experience in embedded software or control systems for robotics and drones.
  • Proficient in Python, C/C++, ROS/ROS2, CAN, MAVLink, Pixhawk, and RTOS.
  • Hardware prototyping, PCB design, raspberry pi a big plusStrong experience with low-level sensor drivers, debugging, and real-time tuning.
  • Familiarity with flight test, telemetry logging, and blackbox analysis.
  • Experience with autonomous systems or swarming protocols.
  • Familiarity with Nvidia Jetson, STM32, or custom SoC platformsCivilian or defense domain UAS work experience.

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