BRINC
Autonomy Engineer, State Estimation & Control
About this role
BRINC seeks a Navigation & Sensing Engineer to develop advanced positioning and multi-sensor fusion algorithms for UAVs deployed in public safety operations. You'll design resilient navigation systems that work in GPS-denied environments, integrating GNSS, inertial sensors, and complementary modalities while collaborating across autonomy and hardware teams.
What you'll do
- Design and implement state estimation algorithms including GNSS/INS fusion and robust filtering techniques
- Develop navigation pipelines integrating multiple sensors (GNSS, IMU, magnetometer, barometer, LiDAR, Radar)
- Create GNSS integrity monitoring and spoofing/jamming detection algorithms with fallback behaviors
- Build sensor calibration, synchronization, and observability pipelines for multi-sensor UAV systems
- Optimize real-time navigation algorithms for embedded processors with focus on efficiency and fault tolerance
- Validate navigation performance through simulation, hardware-in-the-loop testing, and field flight operations
What they're looking for
- C++ and Python programming for real-time systems
- GNSS technologies (RTK, PPP, multi-constellation, L1/L2/L5)
- Multi-sensor fusion and state estimation (Kalman filtering, error-state filtering)
- Embedded systems and real-time compute implementation
- UAV and robotics navigation system development
- GNSS resilience and anti-spoofing/anti-jamming techniques
- Sensor characterization and field validation
- ROS, PX4, MAVSDK, or similar robotics middleware
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BRINC
BRINC builds drone systems and cloud platforms that enable public safety agencies to deploy drones to emergency response situations like 911 calls. The company is hiring for engineering roles across navigation and sensing, electrical systems, RF communications, embedded software, and fullstack web development to support their drone hardware and LiveOps platform.
- Website
- brinc.io
Likely interview questions
- Walk us through your experience implementing state estimation algorithms like EKFs or factor graphs. What challenges did you face, and how did you optimize for real-time performance on embedded systems?
- Describe a project where you developed control algorithms for an unmanned system. How did you validate your designs through simulation, hardware-in-the-loop testing, and real-world flight?