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
What you’ll be doing
Develop cutting-edge reinforcement learning algorithms to enable robust, contact-rich dexterous manipulation, translating vision, depth, tactile, and proprioceptive sensor input into precise end-effector and joint-level motor commands.
Design, test, and refine algorithms to solve complex real-world manipulation challenges, such as handling diverse package form factors, dynamic hand-offs, and operating door handles or latches.
Collaborate with the foundation model team to innovate methods that leverage both simulated and real-world data.
What you must have
- Strong background in robotic manipulation, including dynamics, grasp synthesis, and trajectory optimization.
- Master’s degree or higher in a relevant field such as Engineering, Robotics, or Machine Learning.
- A minimum of five years of industry or research experience, with PhD experience applicable.
- Strong deep learning fundamentals, including supervised and self-supervised learning techniques, and reinforcement learning, including Markov Decision Processes (MDPs), neural network architectures, policy optimization algorithms, model-based vs. model-free RL, exploration-exploitation strategies, value function methods, transfer learning, domain adaptation, sim-to-real transfer, etc.
- Strong background in robotics including autonomy and/or manipulation.
- Experience with deploying artificial neural networks on hardware platforms.
- Ability to write production-level code in modern C++.
- Ability to prototype algorithms and train deep neural networks in Python.
Get some bonus points
- PhD degree in Robotics, Engineering, Computer Science, Machine Learning or a similar discipline, or an equivalent amount of research experience.
Publications at top-tier conferences (e.g., ICRA, IROS, CoRL, RSS) specifically focusing on robotic manipulation, grasping, or contact-rich RL.
Demonstrated experience working with tactile sensing, multi-fingered robotic hands, or bimanual manipulation.
Skills Required
- Master’s degree or higher in Engineering, Robotics, Machine Learning, or a related field
- At least five years of industry or research experience, with applicable PhD experience accepted
- Strong background in robotic manipulation, including dynamics, grasp synthesis, and trajectory optimization
- Strong deep learning fundamentals, including supervised and self-supervised learning
- Strong reinforcement learning knowledge, including MDPs, policy optimization, exploration, value functions, transfer learning, domain adaptation, and sim-to-real transfer
- Strong robotics background in autonomy and/or manipulation
- Experience deploying artificial neural networks on hardware platforms
- Production-level programming ability in modern C++
- Ability to prototype algorithms and train deep neural networks in Python
- PhD in Robotics, Engineering, Computer Science, Machine Learning, or a similar discipline, or equivalent research experience
- Publications at top-tier conferences focused on robotic manipulation, grasping, or contact-rich reinforcement learning
- Experience with tactile sensing, multi-fingered robotic hands, or bimanual manipulation
What We Do
Reality in Virtual Reality Limited is a developer of Virtual Reality assets in both 360 video and photo realistic virtual reality experiences. Offering immersive training for all industries. We scan any real-world environment and use our RiVR VR Simulation Engine and our VRM (Virtual Reality Monitor) to enable cutting edge training anywhere in the world. With our simulation engine we can capture any location and recreate it in photorealistic virtual reality. RiVR allows users to interact with and experience these worlds, enhancing the way humans learn.
