Lead - Autonomy (UAVs)

About the Role<\/span><\/b><\/span><\/span><\/span><\/div>
As the Autonomy Lead<\/b>, you will architect, build, and lead the development of the full autonomy stack\u2014ranging from perception\-informed navigation to path planning and robust control algorithms. You will collaborate closely with our firmware, perception, and systems integration teams to deploy real\-time autonomy solutions on actual flight hardware.
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You will also play a key leadership role: mentoring engineers, driving roadmap decisions, and ensuring high performance and reliability in mission\-critical environments.
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Key Responsibilities<\/span><\/b><\/div>
Architecture & Development<\/b>
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Design and implement core components of the autonomy stack: state estimation<\/b>, motion planning<\/b>, trajectory generation<\/b>, and control<\/b>.
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Drive the integration of perception, mapping, and localization systems into robust navigation algorithms.
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Own the autonomy system architecture<\/b>, ensuring it meets real\-time, safety, and performance constraints.
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Optimize for performance on embedded compute platforms (e.g., NVIDIA Jetson, PX4 Companion Computers).
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Leadership & Strategy<\/b>
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Define the technical roadmap<\/b> for the autonomy team in alignment with product and platform needs.
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Mentor and manage a team of autonomy, controls, and navigation engineers.
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Drive code quality<\/b>, system reliability<\/b>, and testing strategy<\/b>, including simulation\-in\-the\-loop (SITL) and real\-world test flights.
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Represent the autonomy function in cross\-functional meetings with firmware, perception, hardware, and product teams.
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Testing & Deployment<\/b>
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Develop simulation environments for autonomy testing (e.g., Gazebo, AirSim, or custom frameworks).
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Validate algorithms through real\-world flight testing and flight log analysis.
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Collaborate with systems integration engineers to tune algorithms on physical platforms under various flight conditions.
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Research & Innovation<\/b>
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Stay current with state\-of\-the\-art developments in robotics, drone autonomy, and reinforcement learning.
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Evaluate and integrate promising approaches from academia and industry (e.g., learning\-based control, SLAM, dynamic path planning).
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Requirements<\/h3>
Qualifications<\/span><\/b><\/div>
Bachelor\u2019s or Master\u2019s degree in Robotics, Aerospace, Computer Science, or a related field<\/b>.
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6+ years<\/b> of experience in robotics, autonomous systems, or UAV software.
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Strong expertise in at least 2 of the following:
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SLAM / state estimation<\/b>
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Motion planning<\/b> (e.g., RRT*, A*, MPC)
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Control theory<\/b> (PID, LQR, nonlinear control)
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Proficient in C++ and Python<\/b>, with experience in ROS, PX4/Ardupilot integration, and real\-time systems.
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Hands\-on experience with robot simulators<\/b> (e.g., Gazebo, AirSim, Isaac Sim) and flight test environments<\/b>.
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Proven track record of deploying autonomy software on physical platforms.
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Benefits<\/h3>
Why Join Us<\/span><\/b><\/div><\/li>
Work at the forefront of autonomy, AI, and UAV innovation.
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Influence architecture and decisions from the ground up.
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Collaborate with a highly skilled multidisciplinary team.
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Competitive compensation and equity options.
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