Applied Scientist — Safe Autonomy for Robotics

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

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon.com Services LLC in Pasadena, CA is hiring an Applied Scientist to develop core Control Barrier Function algorithms for safety‑critical robotics. You will bridge theory and hardware realities, ensure certifiable safety, and advance CBF theory for Amazon’s robot fleet.

You will collaborate across perception, planning, and manipulation teams to push safe autonomy from learning to deployment. A PhD or Master’s with strong robotics and DL background is required.

Qualifications

• PhD or Master’s with 4+ years of deep learning, computer vision, or robotics experience.
• Deep expertise in Control Barrier Functions and practical implementations.
• Strong math background in dynamical systems and formal verification.
• Proficiency in C++ and Python for real-time control.
• Publications in relevant venues.

Responsibilities

• Develop and implement novel CBF algorithms with formal safety guarantees.
• Compute invariant sets for high‑dimensional robotic systems.
• Design hybrid dynamical system formulations with provable safety.
• Address robustness to model uncertainty and sensor noise.
• Create real‑time optimization solvers for safety‑critical control.
• Contribute to safety certification documentation and standards.
• Validate algorithms through simulation and hardware experiments.
• Collaborate with perception, planning, locomotion teams.

Skills

Control Barrier Functions

C++

Python

Deep learning

Dynamical systems

Formal verification

Real-time control

Publications

Education

PhD or Master’s with 4+ years in DL/robotics

Job description

Amazon.com Services LLC in Pasadena, CA is hiring an Applied Scientist to develop core Control Barrier Function algorithms for safety‑critical robotics. You will bridge theory and hardware realities, ensure certifiable safety, and advance CBF theory for Amazon’s robot fleet.

You will collaborate across perception, planning, and manipulation teams to push safe autonomy from learning to deployment. A PhD or Master’s with strong robotics and DL background is required.