Job SummaryJoin 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
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.
