Applied Scientist II, Industrial Robotics Group

Industrial Robotics Group 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 manipulation, locomotion, and human-robot interaction.

We're seeking an Applied Scientist to join our Robotics team. This role focuses on developing innovative machine learning solutions that enable robots to perform complex manipulation tasks in real-world environments. You will work on creating adaptive learning approaches that combine traditional robotics with modern ML techniques to improve robot performance and reliability. In this role, you will collaborate with multidisciplinary teams to advance the state-of-the-art in robotic manipulation, contributing to the development of next-generation autonomous systems that can operate safely and efficiently within Amazon fulfillment centers.

Key job responsibilities
- Lead design, adapt, and implement novel machine learning solutions for manipulation robots
- Create hybrid approaches combining classical methods with learning-based solutions
- Design learning algorithms for automated parameter tuning and adaptation
- Develop data collection pipelines and methodologies for capturing high-quality demonstrations of dexterous tasks
- Build and test prototype robotic workcell setups to validate the performance of the solution
- Partner with cross-functional teams to rapidly create new concepts and prototypes
- Work with Amazon's robotics engineering and operations teams to grasp their requirements and develop tailored solutions
- Document the architecture, performance, and validation of the final system