We’re building the brains and infrastructure behind autonomous flight. From simulation to real-world flight, we bridge the gap between algorithms and the hardware that they drive.
This role sits at that boundary: turning autonomy concepts into systems that survive contact with reality.
If you like owning messy, end-to-end technical problems and turning theory into things that actually fly, this is your arena.
What you’ll do
As a Senior Autonomous Systems Engineer, you’ll own the autonomy integration layer across simulation and flight. You’ll work closely with computer vision specialists to implement, integrate, test, and deploy autonomy behaviors on real vehicles.
This is a senior role with system-level ownership, not a narrowly scoped feature role.
Your responsibilities include:
Design, build, and own guidance and navigation on top of an ArduPilot flight control implementation.
Extend the ArduPilot firmware.
Develop GCS application to cue interceptors with ground-sensor input.
Develop and maintain the end-to-end autonomy pipeline, covering:
Gazebo-based simulation
SITL, HITL, and real-world flight testing
CI/CD pipelines that validate autonomy in simulation before release
Build tooling for scenario automation, regression testing, and HITL validation
Integrate GNC and mission logic into reliable, end-to-end systems
Contribute to on-board software for navigation, communications, and health monitoring
Own system bring-up, debugging, and verification in Linux-based environments
Collaborate closely with UAV engineers during flight trials and post-flight data analysis
Our Stack (Today)
We’re explicit about this so there’s no guessing:
Simulation: Gazebo
Autopilot: ArduPilot
Vehicle & comms integration: MAVSDK, MAVlink
On-board autonomy: Python on an Nvidia Jetson companion computer
OS: Linux
No ROS
You’re not expected to have used this exact stack before—but you are expected to ramp quickly and apply solid engineering mental models to new tools.
What We’re Looking For
Core Skills
Deep background in software engineering for robotics or autonomous systems
Proven ability to own complex systems end-to-end, from architecture through flight validation
Strong Python experience in production systems (our current autonomy stack is Python)
Comfortable working in Linux-based environments
Hands-on systems mindset: bring-up, debugging, and making things work in the real world
Practical networking experience, including:
Long range RF links
Wi-Fi access point setup
Basic network hardening and reliability for field operations
Diligent, precise engineering style with a bias toward robustness over cleverness
Nice-to-Haves / Pluses
C++ experience - We expect to migrate performance-critical parts of the autonomy stack to C++ over time
Embedded systems experience (e.g. Nvidia Jetson, Raspberry Pi)
Experience with HIL or SIL setups
Familiarity with flight control firmware or autopilot architectures (ArduPilot, PX4, or similar)
Exposure to computer vision pipelines and autonomy-adjacent data workflows
CAD experience, in particular Fusion360
A1–A3 or A2 drone license
(Not required, but supported and considered a perk of the role)
Why join us?
You’ll own the digital half of autonomy: the orchestration, validation, and glue that turns specialist algorithms into real autonomous flight. This is a senior role with real ownership, real systems, and real aircraft.
If you prefer pragmatic engineering over academic purity, and you want to see your work reflected in flight logs instead of papers, you’ll fit right in.
The application process
Our application process consists of three short rounds, including a technical assessment that is respectful of your time. After three rounds, we hope to extend you a great offer. We aim to hire quickly to match the pace of our changing world.
Trusk Technology
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