Perception Engineer

General Atomics Aeronautical Systems; Poway (CA); On-site; USD 81,080 - 141,650; Full time

Job summary

General Atomics Aeronautical Systems, Inc. in Poway, California is seeking a skilled engineer for their Perception group. This role involves designing and implementing real-time Dynamic Environment Models (DEM) supporting multi-sensor fusion in advanced unmanned systems.

The ideal candidate will have extensive experience with C++ and Python, along with a strong background in multi-sensor systems. The position is full-time with a competitive salary range of $81,080 - $141,650.

Qualifications

• 5+ years of experience in machine learning engineering with a bachelor's degree.
• 3+ years of experience with a master's degree may be considered.
• Ability to obtain and maintain a DOD security clearance.

Responsibilities

• Build and optimize real-time DEM data structures.
• Implement deterministic fusion + perception infrastructure.
• Support tracking engineers in various models.
• Design and maintain low-latency transport systems.
• Develop tools for evaluation, testing, and visualization.
• Collaborate closely with engineering teams.
• Contribute to sim-to-real validation.

Skills

C++

Python

Multi-sensor fusion

Real-time systems

Kalman-family filters

Memory optimization

Education

Bachelors, Masters degree or PhD in Computer Science, Engineering, Mathematics or a related technical discipline

Tools

ZMQ

DDS

ROS2

Job description

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.

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

EEO Statement

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