Senior Robotics Simulation Scientist – Physics-Based & RL

Amazon; Bellevue (WA); Presencial; USD 167 000 - 226 000; Tempo integral

Resumo da oferta

Amazon is seeking a Simulation Applied Scientist to advance physics-based simulation for robotics. The role blends research and engineering to reduce the sim-to-real gap and translate ideas into production-ready capabilities validated on hardware.

You will work at the intersection of theory and practice, contributing to a platform that enables robots to learn, adapt, and operate safely in real-world environments.

Qualificações

• PhD in Computer Science, Robotics, Mechanical Engineering, or related field.
• Strong publication record in simulation, robotics, or computer graphics.
• Demonstrated ability to advance state of the art through novel research.

Responsabilidades

• Advance physics-based simulation fidelity for contact-rich manipulation and locomotion.
• Design and build high-performance simulation tools integrated into a production robotics stack.
• Translate research ideas into robust, scalable software pipelines.
• Develop methods to quantify and reduce simulation-to-reality gaps across design, safety, and control.
• Architect scalable simulation solutions for rigid and deformable body dynamics.
• Build simulation pipelines optimized for large-scale reinforcement and policy learning.
• Establish frameworks for continuous simulation improvement using real-world deployment data.
• Collaborate with engineering, science, and safety teams on simulation requirements and validation.

Conhecimentos

Java

C++

Python

Publications

Formação académica

PhD in Computer Science / Robotics / Mechanical Engineering

Ferramentas

MuJoCo

Isaac Lab

Drake

Newton

Descrição da oferta de emprego

Amazon is seeking a Simulation Applied Scientist to advance physics-based simulation for robotics. The role blends research and engineering to reduce the sim-to-real gap and translate ideas into production-ready capabilities validated on hardware.

You will work at the intersection of theory and practice, contributing to a platform that enables robots to learn, adapt, and operate safely in real-world environments.