Applied Scientist II, Body Control
Listed on 2026-05-28
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Engineering
Robotics
Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine cutting-edge AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at an unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic dexterous manipulation, locomotion, and human-robot interaction.
This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.
At Amazon we leverage advanced robotics, machine learning, and artificial intelligence to solve complex operational challenges at an unprecedented scale. Our fleet of robots operates across hundreds of facilities worldwide, working in sophisticated coordination to fulfill our mission of customer excellence.
The ideal candidate will contribute to research that bridges the gap between theoretical advancement and practical implementation in robotics. You will be part of a team that's revolutionizing how robots learn, adapt, and interact with their environment.
Key Job Responsibilities- Design and implement whole body control methods for balance, locomotion, and dexterous manipulation
- Utilize state‑of‑the‑art methods in learned and model‑based control
- Create robust and safe behaviors for different terrains and tasks
- Implement real‑time controllers with stability guarantees
- Collaborate effectively with multi‑disciplinary teams to co‑design hardware and algorithms for loco‑manipulation
- Mentor junior engineer and scientists
- PhD, or Master's degree and 2+ years of applied research experience
- Experience with imitation learning and reinforcement learning for whole‑body control
- Experience with methods such as hierarchical quadratic programming and model‑predictive control
- Experience with simulation environments such as Isaac Lab, Mujoco, Drake, etc.
- Experience with developing and deploying code for real‑time controllers
- Experience in state estimation from multiple sensor modalities
- Experience in Java, C++, Python, or a related language
- Experience working effectively across cross‑functional teams and partnering well with people at all levels within an organization
- PhD in Robotics, with a focus on whole‑body control
- Experience with low‑level joint torque/impedance control
- Experience with teleoperation systems
- Experience with robotics frameworks for fast prototyping (Matlab, ROS, etc.)
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