Senior Staff Engineer, Autonomy Integration (R5441)

What you'll do:

Coordinate software and hardware integration activities that enable the autonomy team to deploy and test their stack across a range of platforms, including small UAS, manned fixed-wing aircraft, and unmanned fixed-wing surrogate platforms.
Drive sensor selection for EO/IR and A-PNT perception software testing on operationally relevant or surrogate platforms; support flight test engineers in sensor bring-up, characterization, calibration, and maintenance. 
Own the fly-fix-fly cycle for autonomy and perception software: integrate the Hivemind Pilot stack onto target hardware, verify correct deployment and configuration, define test objectives for flight test campaigns, help execute tests in the field, and analyze collected data to determine pass/fail status against objectives.  
Own sensor calibration and time synchronization processes for all A-PNT and perception sensors used in testing, including camera intrinsic/extrinsic calibration and camera-IMU temporal alignment. 
Establish data quality standards and curate data management processes for field-collected sensor data, ensuring that recordings from flight test campaigns are usable for offline analysis and algorithm development. 
Resolve technical and logistical ambiguities at the boundary between software development and flight test operations, and make command decisions that keep perception maturation efforts moving forward.

Required qualifications:

Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
Hands-on experience calibrating and time-aligning EO/IR and position, navigation, and timing (PNT) sensors, including both COTS and military-grade hardware.
Demonstrated ability to thrive in fast-paced field testing environments, with comfort operating at the intersection of hardware, software, and flight operations.
Experience in design of experiments, flight test card development, and establishing verifiable, measurable test objectives.
Experience deploying perception or autonomy software to edge hardware platforms (e.g., NVIDIA Jetson or comparable embedded compute).
Proficiency in Python for data analysis and visualization; comfort reading and making targeted modifications to algorithms implemented in C++.
Track record of solving problems that span hardware, software, and engineering capacity constraints across functional or organizational boundaries.
Demonstrated academic training or professional experience in a core perception discipline such as object detection, object tracking, SLAM, or navigation, preferably in a defense or aerospace context.

Preferred qualifications:

Experience with camera calibration frameworks (e.g., Kalibr) and camera-IMU extrinsic and temporal calibration workflows.
Familiarity with rosbag-based data collection, replay, and analysis pipelines in robotics or autonomy systems.
Experience characterizing EO/IR gimbal cameras, including MTF, distortion, and radiometric properties.
Background supporting DoD or defense aviation programs, including experience operating under controlled airspace or range environments.
Familiarity with Conan-based, Nix-based, or CMake-based build systems and embedded Linux development.
Experience with CI/CD pipelines and test automation in the context of embedded software.

This role is hybrid, based at Shield AI's San Diego, CA headquarters (three days per week in office), with periodic travel to flight test sites required.