Drone Autonomy Integration Engineer

Applied Intuition

Sunnyvale (CA)

On-site

USD 140,000 - 210,000

Full time

14 days+
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Benefits offered by this job

Relocation offered
Competitive compensation package
Comprehensive benefits

Job summary

Applied Intuition is seeking an Autonomy Integration Engineer to bridge hardware, edge software, and field flight operations. The role is split roughly 50/50 between lab work and live flight activities, with relocation options to support multiple sites including Sunnyvale, FL, or Fort Walton Beach.

You will configure embedded Linux, deploy containerized stacks, and ensure subsystems communicate reliably in real-world tests.

Qualifications

  • 5+ years of experience in robotics integration, flight test engineering, embedded systems, or autonomous vehicles.
  • Bachelor's degree or equivalent combination of education and work experience.
  • Strong Linux CLI, scripting, and containerized deployments (Docker).
  • Hands-on hardware skills: soldering, wiring, diagnostics with multimeters/oscilloscopes.

Responsibilities

  • Lead system bring-up for unmanned aerial systems from benchtop to active flight test campaigns.
  • Deploy and configure edge software and Docker-based stacks across onboard computes.
  • Troubleshoot vehicle networks, sensors, and interfaces in real time.
  • Develop Python/C++ scripts for data analysis, testing, and validation.
  • Fabricate wiring harnesses and define system architecture with clear diagrams.
  • Configure IP routing and networks between flight controllers, radios, and ground control.

Tools

PX4
ArduPilot
Docker
Linux
Python
C++

Job description

Applied Intuition is seeking an Autonomy Integration Engineer to bridge hardware, edge software, and field flight operations. The role is split roughly 50/50 between lab work and live flight activities, with relocation options to support multiple sites including Sunnyvale, FL, or Fort Walton Beach.

You will configure embedded Linux, deploy containerized stacks, and ensure subsystems communicate reliably in real-world tests.

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