You will work on the deployment of LiDAR based SLAM systems in production-level products.
Responsibilities
· Design and implement state-of-the-art LiDAR SLAM algorithms for real-time localization and mapping using multi-sensor inputs (e.g., LiDAR, IMUs, GNSS, wheel encoders).
· Improve the 3D LiDAR mapping accuracy in urban environments.
· Implement robust motion estimation, feature matching, loop closure, and map optimization pipelines.
· Apply non-linear optimization and filtering techniques (e.g., bundle adjustment, graph SLAM, EKF) to maximize system accuracy and robustness.
· Evaluate and benchmark system performance using large-scale datasets and real-world driving scenarios.
· Contribute to system integration, continuous validation, and deployment of SLAM modules on autonomous vehicle platforms.
Qualifications
· PhD degree in computer vision, robotics, or a related field
· Minimum of 2 years of industrial or postdoctoral experience in SLAM, localization, or robotic perception
· Deep theoretical and practical understanding of SLAM systems, 3D geometry, and sensor fusion
· Hands-on experience with real-world datasets and deployment of SLAM pipelines in field environments
· Proficiency in modern C++ and Python, with strong software engineering practices
· Experience with optimization libraries (e.g., g2o, Ceres Solver) and robotics frameworks (e.g., ROS)
About the Company
PolyExplore Inc ( is a growing startup in Silicon Valley with the goal of providing high-precision, low-cost navigation solutions to emerging technologies such as autonomous driving, HD mapping, and unmanned systems, as well as to support and fuel the rapid expansion of the existing precise navigation applications. PolyExplore serves a diverse and rapidly growing group of customers ranging from Silicon Valley startups to Fortune 500 companies. The overall value, as well as performance, service, and reliability, make PolyExplore a leading supplier of navigation solutions.
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