2 months ago
Zürich, SwitzerlandMid Level
Responsibilities
- Develop online and offline localization and SLAM algorithms using camera, LiDAR, IMU, GNSS, and other sensor inputs.
- Design, validate, and improve algorithms on challenging real-world data.
- Contribute to dynamic environmental mapping from continuously collected robot-deployment data.
- Help create robust sensor-calibration systems for complex and unpredictable environments.
- Support workflows for capturing ground-truth data and deployment-site maps for algorithm evaluation.
- Implement deployment-ready code optimized for the robot’s computational constraints.
- Create and maintain documentation and best practices for knowledge sharing.
Requirements
- Master’s degree in robotics, machine learning, computer science, or a similar relevant field.
- 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.
- Ability to write production-level modern C++ and prototype efficiently in Python.
- Experience deploying SLAM or localization algorithms on hardware platforms.
- Experience with state-of-the-art deep learning algorithms for SLAM and localization is a bonus.
- Publications at top-tier conferences are a bonus.
- Experience with ROS or ROS2 is a bonus.
Benefits
- The role requires in-person work at the company’s office locations.
- Employees join a diverse and inclusive robotics team within RIVR, part of Amazon.
