GNC Engineer, Tracking Level 2

About the Role

We are looking for a software engineer focused on real-time tracking, state estimation, and multi-sensor fusion for embedded autonomous systems. This role sits at the intersection of guidance/navigation, computer vision, and real-time software engineering.

You will develop robust target tracking and estimation pipelines that operate under challenging real-world conditions including noisy measurements, intermittent detections, high dynamics, latency, dropped frames, and constrained compute environments. The ideal candidate has strong fundamentals in estimation theory and probabilistic systems, while also understanding the realities of interfacing with modern computer vision stacks running on embedded GPU platforms.

• Design and implement real-time tracking and state estimation algorithms for airborne and autonomous systems
• Develop and maintain multi-target tracking pipelines using camera, IMU, and additional sensor inputs
• Implement filtering and sensor fusion algorithms including:
  • Extended Kalman Filters (EKF)
  • Unscented Kalman Filters (UKF)
  • Particle Filters
  • IMM / Multiple-Model Estimators
  • Smoothing and probabilistic estimation methods
• Build robust track management systems including:
  • Track initiation and deletion
  • Measurement gating
  • Data association
  • Covariance management
  • Occlusion handling
  • Track confidence scoring
• Interface tracking systems with modern computer vision pipelines and detectors
• Integrate asynchronous measurements from heterogeneous sensors with differing latencies and update rates
• Optimize algorithms for embedded compute platforms including NVIDIA Jetson-class hardware
• Develop low-latency real-time software in C++ for deployment in operational environments
• Work closely with guidance, autonomy, perception, and controls engineers
• Build simulation and replay environments for estimator validation and performance analysis
• Analyze estimator stability, observability, and numerical robustness under degraded conditions

• BS/MS in Computer Science, Aerospace Engineering, Electrical Engineering, Robotics, Applied Mathematics, Physics, or related field
• Strong experience with state estimation, tracking, or sensor fusion systems
• Strong C++ software engineering experience
• Experience implementing real-time systems on Linux
• Solid understanding of:
  • Linear algebra
  • Probability and statistics
  • Coordinate frames and transformations
  • Kinematics and dynamics
  • Numerical methods
• Experience with one or more of the following:
  • Multi-object tracking
  • Visual-inertial estimation
  • SLAM
  • Radar tracking
  • EO/IR tracking systems
  • Guidance and navigation systems
• Familiarity with computer vision pipelines and detector outputs
• Experience consuming outputs from CV frameworks such as:
  • TensorRT
  • Deep Stream
  • OpenCV
  • PyTorch/TensorRT inference pipelines
• Experience debugging noisy real-world sensor systems

• Experience with embedded GPU platforms (Jetson Xavier, Orin, CUDA)
• Familiarity with EO/IR sensor systems
• Experience with asynchronous sensor timing and synchronization
• Experience building high-rate telemetry or distributed real-time systems
• Understanding of:
  • Bayesian filtering
  • Multi-hypothesis tracking
  • JPDA/MHT approaches
  • Optical flow
  • Visual odometry
• Familiarity with ROS2, GStreamer, or Deep Stream pipelines
• Experience with hardware interfaces such as:
  • CAN
  • UART/RS232
  • Ethernet UDP/TCP
  • MIPI CSI-2
• Experience with simulation environments and hardware-in-the-loop testing
• Prior aerospace, defense, or autonomous systems experience

• Real-time target tracking systems operating on embedded edge hardware
• High-rate fusion of EO/IR detections with inertial navigation systems
• Low-latency estimator pipelines for autonomous guidance applications
• Robust tracking systems resilient to clutter, dropped detections, and degraded sensing environments
• Tight integration between perception, estimation, and control subsystems

You are someone who enjoys bridging theory and deployment reality. You understand that good tracking performance comes not only from elegant filtering equations, but also from robust software architecture, timing discipline, sensor characterization, and operational awareness.

You are comfortable debugging systems where detector confidence, latency, dropped packets, motion blur, and estimator divergence all interact simultaneously — and you know how to build systems that remain stable and performant anyway.

• CUDA acceleration
• GPU-accelerated vision pipelines
• Real-time Linux optimization
• Object detection and classification systems
• RF or radar tracking
• Flight software or autonomy stacks
• Distributed sensor systems
• Tactical networking and telemetry systems

• Competitive salary and equity package
• High ownership and technical autonomy
• Opportunity to work on advanced autonomous systems
• Access to cutting-edge embedded compute and sensing hardware
• Fast-paced engineering environment with direct mission impact

• To conform to U.S. Government export regulations, applicant must be a (i) U.S. citizen or…