Senior Vision-based Navigation Engineer
📍 Location: Dallas, Texas
Pushing the Boundaries of Sensor Fusion Technology
Our client is at the forefront of developing cutting-edge multi-sensor fusion solutions for high-precision navigation. With a focus on inertial navigation, GNSS integration, and vision-based state estimation, their R&D team is dedicated to advancing sensor fusion algorithms for aerospace, defense, robotics, and autonomous systems.
The Role
We are looking for a Senior Navigation Engineer to lead the research, design, and implementation of advanced sensor fusion algorithms. In this role, you’ll work at the intersection of state estimation, sensor modeling, and real-time data integration, helping develop next-generation navigation systems. As projects evolve, you may have the opportunity to build and lead a small technical team.
Key Responsibilities
✅ Develop and optimize state estimation and multi-sensor fusion algorithms for high-precision navigation.
✅ Design tightly-coupled sensor fusion solutions integrating IMU, GNSS, vision-based navigation, and ranging technologies.
✅ Implement and test algorithms in MATLAB and Python, performing rigorous simulations and performance analysis.
✅ Work with sensor modeling techniques to improve accuracy and robustness in challenging environments.
✅ Collaborate with a high-caliber R&D team to transition algorithms from research to working prototypes.
✅ Potentially lead and mentor a specialized team as projects move toward commercialization.
What We’re Looking For
🔹 10+ years of experience in multi-sensor fusion and state estimation, or 5+ years with strong expertise in vision-based navigation.
🔹 Deep knowledge of state estimation techniques (e.g., Kalman filters, factor graphs, error-state filtering).
🔹 Experience developing tightly-coupled sensor fusion algorithms for IMU, GNSS, and vision-based navigation.
🔹 Strong programming and simulation skills in MATLAB and Python.
🔹 Familiarity with vision-based navigation methods (e.g., feature tracking, SLAM, optical flow) is a plus.
