Applied Scientist, Safe Control, Amazon Robotics, Compass

Job description

We are seeking an Applied Scientist to join Compass. In this role, you will develop the core Control Barrier Function (CBF) algorithms that form the mathematical foundation of the Compass safety system. You will ensure they don't just work in theory but perform reliably on real robots under real-world conditions. You will push the boundaries of concepts central to CBFs: computing robust invariant sets, designing hybrid system formulations that handle contact transitions and mode switches, and developing backup-set approaches that leverage learned policies and multiple controllers.

Key job responsibilities • Develop and implement novel CBF algorithms that provide formal safety guarantees…

Job requirements

PhD, or Master's degree and 4+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience
Deep expertise in Control Barrier Functions, including theoretical foundations and practical implementation
Strong mathematical background in dynamical systems theory, nonlinear control, and formal verification or reachability analysis
Proficiency in C++ and Python with experience implementing control algorithms for real-time systems
Publication record at relevant venues (e.g., CDC, ACC, ICRA, RSS, Automatica, TAC)
Experience in professional software development
Experience validating safety-critical algorithms on physical robotic hardware (not simulation-only)
Experience with hybrid systems theory and formulations that handle discrete transitions (e.g., contact events, mode switches)

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