Sobre esta vaga de SLAM / Computer Vision Intern na Rivr
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, part of Amazon 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.
Important Notice: For this position, we can unfortunately only accept applications from citizens of Schengen Area countries. This restriction does not apply to ETHZ and EPFL students who are required to complete compulsory internships as part of their studies.Job Description
As a SLAM Intern, you will join our team to advance the localization and mapping capabilities of our last-mile delivery robot. Your work will directly shape how our robot perceives and navigates complex urban environments — from benchmarking existing approaches to prototyping novel algorithms and validating them on hardware. This role offers hands-on experience in spatial perception, algorithm development, and real-world deployment within a dynamic and collaborative environment. We are committed to finding and nurturing exceptional talent; our internships are a key pathway to recruiting outstanding graduates who can make a significant impact in our team.
What you'll be doing
Work closely with senior engineers to integrate SLAM modules with hardware components and contribute ideas to enhance system robustness and accuracy.
Support the team in benchmarking, evaluating, and developing novel state-of-the-art localization and mapping algorithms for robotic applications.
Engage in continuous learning and gain exposure to recent developments from the SLAM and computer vision literature.
What you should have
At least a BSc in Computer Science, Robotics, Engineering, or equivalent discipline.
Previous coursework or projects related to computer vision, SLAM, or 3D geometry.
Experience with C++ and / or Python.
Eagerness to learn and contribute in a team environment.
Strong problem-solving and analytical skills.
Get some bonus points
Proven experience implementing or extending SLAM systems.
Exposure to state of the art dense visual SLAM or multi-view stereo approaches.
Familiarity with sensor fusion techniques involving cameras, LiDAR, or IMUs.
Knowledge of relevant frameworks or libraries such as OpenCV, GTSAM, Ceres, Eigen, or similar.
Experience with ROS/ROS 2 and real-world robotic data collection.
