Senior SLAM Engineer

We are looking for the best
As a Senior SLAM Engineer at 42dot, you will lead the development of advanced localization and mapping technologies that form the foundation of autonomous driving. Leveraging cutting-edge geometric vision techniques, you will design robust SLAM pipelines that fuse data from multiple sensors to estimate the vehicle's pose and reconstruct its surroundings in real-time. You will work closely with cross-functional teams across perception, planning, and robotics to ensure the seamless integration and deployment of SLAM systems in production-level autonomous vehicles.

Responsibilities

• Design and implement state-of-the-art SLAM algorithms for real-time localization and mapping using multi-modal sensor inputs (e.g., cameras, IMUs, GPS, wheel encoders).
• Develop robust online and offline state estimation methods for complex urban and highway environments.
• Focus on 3D geometric vision problems such as VSLAM, VIO, SfM, and scene reconstruction.
• 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.
• Collaborate with sensor calibration and perception teams to improve system performance and consistency.
• 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.
• Mentor junior engineers and contribute to technical leadership within the team.

Qualifications

• PhD degree in computer vision, robotics, or a related field is a plus
• 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)

Preferred Qualifications

• Experience in large-scale autonomous driving or robotics system development
• Familiarity with sensor modeling and calibration for cameras, IMUs, GPS, and wheel encoders
• Expertise in real-time performance optimization, multi-threading, and hardware acceleration (GPU, SIMD)
• Contributions to open-source SLAM libraries or publications in top-tier conferences (e.g., ICRA, CVPR, RSS)Experience with mapping infrastructure, map maintenance, and life-long localization
• Strong communication skills and ability to collaborate across multidisciplinary teams

※ Please review the following information before applying.
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