Perception Engineer Job at General Atomics Aeronautical Systems in Poway
General Atomics Aeronautical Systems, Poway, CA, United States
Job Summary
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.
Job Qualifications
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.
Job Type: Full‑Time Salary
Salary range: 81,080 - 141,650
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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.
Job Qualifications
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.
Job Type: Full‑Time Salary
Salary range: 81,080 - 141,650
#J-18808-Ljbffr