Engineer III

General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.

Join our Perception group to design and implement a real-time Dynamic Environment Model (DEM) to support multi-sensor fusion, track management, and sensor resource management across advanced unmanned systems. This role will design and implement the perception and fusion infrastructure that aggregates radar, EO/IR, ESM, and other sensor inputs into a coherent, uncertainty-aware spatiotemporal world model, enabling high-confidence situational awareness and autonomous decision-making. This role focuses on real-time systems, probabilistic fusion, tracking, data structures, and performance-critical C++.

DUTIES AND RESPONSIBILITIES:

• Build and optimize real-time DEM data structures:

• Spatiotemporal voxel grids / occupancy & belief fields

• Confidence, decay, and provenance tracking

• Implement deterministic fusion + perception infrastructure:

• Sensor synchronization, buffering, time alignment, calibration

• Real-time data association and multi-sensor integration

• Support tracking engineers implementing IMM-EKF/UKF, JPDA, and data association models

• Design and maintain low-latency transport (ZMQ/DDS/ROS2, shared memory, lock-free queues)

• Develop tools for:

• Replay and Monte-Carlo evaluation

• Field test debug & metrics

• Live introspection and visualization of DEM states & tracks

• Collaboration

• Work closely with:

• Tracking & state estimation engineers

• ML engineers building feature and occupancy networks

• Autonomy stack and mission systems teams

• Contribute to sim-to-real validation

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

• Typically requires a bachelors, masters degree or PhD in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and progressive machine learning engineering experience as follows; five or more years of experience with a bachelors degree or three or more years of experience with a masters degree. May substitute equivalent machine learning engineer experience in lieu of education.

• Strong C++ and Python

• Experience with:

• Multi-sensor fusion (IR/Radar/ESM ideal)

• Real-time systems, concurrency, memory optimization

• Kalman-family filters and uncertainty modeling

• Familiarity with:

• JPDA / multi-target tracking frameworks

• DDS / ZMQ / ROS2 or similar messaging

• Spatiotemporal mapping or occupancy grid systems

• STAP/DPCA basics or RF signal chain awareness

• Ability to obtain and maintain a DOD security clearance required.