Applied & Research Scientist — Safe Autonomy Frontiers

Amazon Science; Pasadena (CA); Sur place; USD 143 000 - 193 000; Plein temps

Avantages offerts par ce poste

Health insurance

401(k) matching

Paid time off

Parental leave

Résumé du poste

Amazon Science's Safe Autonomy Frontiers (SAF) Lab is recruiting Applied and Research Scientists to advance safe autonomy for dynamic robots, combining foundational research with hardware deployment across locomotion and manipulation. You will work on CBF theory, safe RL, and layered safety filters, validating on state-of-the-art hardware and contributing to Amazon’s scientific leadership.

You will publish at top venues and help translate research into scalable deployments, collaborating with

Qualifications

• PhD or equivalent research experience.
• Master’s degree with 3+ years of applied science/robotics experience OR PhD in related field.
• Hands-on experience deploying control algorithms and learning policies on physical robots.
• Working knowledge of safety-critical control, including control barrier functions.
• Proficiency in C++ and Python with real-system implementations.
• Experience with robotics simulators such as Isaac Gym/Sim, MuJoCo, PyBullet.
• Publications or patents in top robotics or ML venues.

Responsabilités

• Advance safe autonomy from formal foundations to hardware validation.
• Test and validate hardware on locomotion and manipulation systems.
• Bridge theory and practice to drive next research cycles.
• Publish research in top robotics, control, and ML venues.
• Collaborate with SAF Lab and Amazon production teams to deploy research at scale.

Connaissances

C++

Python

Robotics

Control theory

Research publication

Hardware deployment

Formation

Master's degree

PhD

Outils

Isaac Gym/Sim

MuJoCo

PyBullet

Description du poste

Amazon Science's Safe Autonomy Frontiers (SAF) Lab is recruiting Applied and Research Scientists to advance safe autonomy for dynamic robots, combining foundational research with hardware deployment across locomotion and manipulation. You will work on CBF theory, safe RL, and layered safety filters, validating on state-of-the-art hardware and contributing to Amazon’s scientific leadership.

You will publish at top venues and help translate research into scalable deployments, collaborating with