Senior Applied Scientist, Amazon Industrial Robotics

Amazon Industrial Robotics 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 Industrial Robotics 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.

Join us in building the next generation of intelligent robotics systems that will transform the future of automation and human-robot collaboration.

Key job responsibilities
- Collaborate with simulation and robotics experts to translate physical modeling needs into robust, scalable, and maintainable simulation solutions.
- Design and implement high-performance simulation modeling and tools for rigid and deformable body simulation.
- Identify and optimize performance bottlenecks in simulation pipelines to support real-time and batch simulation workflows.
- Help build validation and unit testing pipelines to ensure correctness and physical fidelity of simulation results.
- Identify potential sources of sim-to-real gaps and propose modeling and numerical approximations to reduce them.
- Stay current with the latest advances in numerical methods, parallel computing, and GPU architectures, and incorporate them into our tools.