SLAM Software Engineer

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SLAM Software Engineer

RIVR

Location

Zürich

Experience

Mid

Posted

Jul 10, 2026

Apply by

August 9, 2026

Applicants

0

Early applicantEasy applyFull-timeWork from Office

Job Description

RIVR, part of Amazon is a robotics company pioneering Physical AI through real-world doorstep delivery. Founded in 2024 as an ETH Zurich spin-off, RIVR developed wheeled-legged robots designed to operate in complex, unstructured environments such as stairs, gates, doors, and uneven urban terrain. We believe that achieving general physical intelligence requires solving real customer problems in the real world, where robots can learn from rich operational data at scale. Following our acquisition by Amazon in March 2026, we are continuing this mission with greater reach and speed. By combining custom robot hardware, onboard autonomy, and cloud-based coordination, RIVR, part of Amazon is building the next generation of safe, reliable autonomous robots for last-mile delivery ### Job Description Our robots require precise and real-time localization, which they achieve by utilizing onboard sensors such as IMUs, lidar, cameras and GNSS. In environments without existing maps, the robot must dynamically create a map while simultaneously localizing itself within it. As our next SLAM Engineer on a growing team, you will be an expert in laser- and camera-based localization techniques and SLAM and enhance these capabilities. You will shape our robots’ ability to navigate with pinpoint precision, and you will be part of a team focused on enabling our robots to navigate autonomously. If you are passionate about robotics and driven to innovate in SLAM and localization, we encourage you to join us in shaping the future of intelligent robotics. ### Responsibilities - Develop state-of-the-art, online and offline localization and SLAM algorithms by fusing information from cameras, LiDARs, IMU, GNSS, and other sensors. - Design, validate, and improve algorithms on challenging real-world data. - Contribute to the dynamic mapping of the environment using data continuously gathered from ongoing robot deployments. - Assist in the creation of robust sensor calibration systems that perform reliably in complex and unpredictable environments. - Support the development of an efficient workflow to accurately capture ground truth data, and maps of deployment sites for algorithm evaluation. - Contribute to the implementation of deployment-ready code for the real robot, optimized for the robot’s computational constraints. - Create and maintain documentation and best practices to streamline knowledge sharing. ### What you must have - Master’s degree in a relevant field such as Robotics, Machine Learning, Computer Science, or a similar discipline. - A minimum of 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 mathematical fundamentals including linear algebra, vector calculus, probability theory, and mathematical optimization. - Ability to write production-level code in modern C++, and prototype efficiently in Python. - Experience with deploying SLAM or localization algorithms on hardware platforms. ### Get some bonus points - Experience with state of the art deep learning algorithms for SLAM and localization. - Publications at top-tier conferences. - Experience with ROS/ROS2. RIVR, part of Amazon is committed to building a diverse and inclusive team that values every perspective. If you’re passionate about driving innovation in robotics and creating meaningful impact, we encourage you to apply and bring your unique self to our team. We believe the best work is done when collaborating and therefore require in-person presence in our office locations.

Key Responsibilities

  • Develop online and offline localization and SLAM algorithms by fusing data from cameras, LiDARs, IMUs, and GNSS.
  • Design, validate, and improve algorithms using challenging real-world data.
  • Contribute to dynamic mapping of environments using data from ongoing robot deployments.
  • Assist in creating robust sensor calibration systems for complex environments.
  • Support the development of efficient workflows to capture ground truth data and maps.
  • Implement deployment-ready code optimized for robot 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 discipline

Skills Required

C++PythonSLAMLocalizationComputer VisionLiDARIMUGNSSLinear AlgebraVector CalculusProbability TheoryMathematical Optimization3D Visual SLAMPlace RecognitionStructure from MotionFilteringBayesian EstimationCollaborationProblem SolvingDeep LearningROSROS2

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