Senior Scientist, Safe Autonomy for Robotic Systems

Amazon Science; Pasadena (CA); Presencial; USD 167 000 - 226 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Health insurance

401(k) matching

RSU program

Paid time off

Resumo da oferta

Amazon Science seeks Applied and Research Scientists for the Safe Autonomy Frontiers Lab. You will advance safe autonomy on dynamic robots, validating theory on hardware and publishing at top venues.

Responsibilities include testing locomotion and manipulation, bridging theory to practice, and collaborating across SAF Lab and production teams to scale deployments. The role emphasizes CBF theory, safe reinforcement learning, and layered safety filters, with experiments on state-of-the-art robotic

Qualificações

• PhD or Master’s degree with 3+ years of relevant research experience in robotics or a related field.
• Hands-on experience deploying control algorithms or learning policies on physical robotic hardware.
• Strong knowledge of safety-critical control and learning-based integration.

Responsabilidades

• Advance safe autonomy from formal foundations to hardware validation on robots.
• Test and validate locomotion, manipulation, and loco-manipulation on hardware.
• Bridge theory and practice to drive next research cycles.
• Publish at top robotics, control, and ML venues and enhance Amazon’s scientific reputation.
• Collaborate with SAF Lab and Amazon teams to deploy research at scale.

Conhecimentos

CBF theory

Safe RL

Control algorithms

C++

Python

Robotics hardware

Perception integration

Formação académica

PhD or MS in CS/Robotics

Ferramentas

Isaac Gym

MuJoCo

PyBullet

Python

C++

Descrição da oferta de emprego

Amazon Science seeks Applied and Research Scientists for the Safe Autonomy Frontiers Lab. You will advance safe autonomy on dynamic robots, validating theory on hardware and publishing at top venues.

Responsibilities include testing locomotion and manipulation, bridging theory to practice, and collaborating across SAF Lab and production teams to scale deployments. The role emphasizes CBF theory, safe reinforcement learning, and layered safety filters, with experiments on state-of-the-art robotic