1 day ago
Zürich, SwitzerlandMid Level
Responsibilities
- Develop online and offline localization and SLAM algorithms by fusing camera, LiDAR, IMU, GNSS, and other sensor data.
- Design, validate, and improve algorithms using challenging real-world data.
- Contribute to dynamic environmental mapping from robot deployment data.
- Create robust sensor calibration systems for complex environments.
- Develop workflows for capturing ground-truth data and deployment-site maps for algorithm evaluation.
- Implement deployment-ready code optimized for the robot’s computational constraints.
- Document algorithms and maintain best practices for knowledge sharing.
Requirements
- At least 3 years of industry or research experience.
- Background in computer vision, robotics, or autonomous driving, with experience in areas such as 3D visual or LiDAR SLAM, place recognition, structure from motion, filtering, or Bayesian estimation.
- Strong foundations in linear algebra, vector calculus, probability theory, and mathematical optimization.
- Production-level modern C++ programming and efficient Python prototyping skills.
- Experience deploying SLAM or localization algorithms on hardware platforms.
- Master’s degree in Robotics, Machine Learning, Computer Science, or a similar relevant field.
- Preferred: experience with state-of-the-art deep-learning algorithms for SLAM and localization, publications at top-tier conferences, and ROS/ROS2 experience.
About Amazon
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