Safe Autonomy Scientist: CBF & RL for Dynamic Robots

Amazon Inc.; Pasadena (CA); On-site; USD 143,000 - 193,000; Full time

Job summary

Amazon's Safe Autonomy Frontiers Lab seeks Applied and Research Scientists to advance safe autonomy on dynamic robots, from theory to hardware deployment. You will work on CBF, safe RL, and layered safety filters with perception and learning components.

The role involves validating on hardware platforms, publishing in robotics venues, and collaborating across SAF Lab and Amazon teams to scale deployment of safe autonomy at Amazon's scale.

Qualifications

• PhD or equivalent research experience.
• Master’s +3 years in CS/ robotics/ control or related field, OR PhD.
• Hands-on experience developing and deploying control algorithms on physical robotic hardware in a research or production setting.
• Proficiency in C++ and Python with real systems.
• Experience with physics simulators for robotics (Isaac Gym/Sim, MuJoCo, PyBullet).
• Demonstrated technical impact through shipped systems, patents, or publications at top-tier venues.

Responsibilities

• Advance safe autonomy research from formal foundations to hardware validation.
• Test and validate hardware focusing on locomotion, manipulation, and loco-manipulation.
• Bridge theory and practice to guide next research cycle and deployments.
• Publish research in top robotics, control, and ML venues.
• Collaborate with SAF Lab and Amazon teams to scale deployments.

Skills

Robotics hardware deployment

Safety-critical control

Cross-functional collaboration

Strong communication

Education

PhD or equivalent research experience

Master’s +3 years in CS/ robotics/ control or related field, or PhD

Tools

C++

Python

Isaac Gym/Sim

MuJoCo

PyBullet

Job description

Amazon's Safe Autonomy Frontiers Lab seeks Applied and Research Scientists to advance safe autonomy on dynamic robots, from theory to hardware deployment. You will work on CBF, safe RL, and layered safety filters with perception and learning components.

The role involves validating on hardware platforms, publishing in robotics venues, and collaborating across SAF Lab and Amazon teams to scale deployment of safe autonomy at Amazon's scale.