Applied Scientist, Safe Control, Amazon Robotics, Compass
Core
Develop Control Barrier Function (CBF) algorithms to ensure safe, reliable operation of robots under real-world conditions, bridging mathematical theory with hardware implementation.
Role type
Applied Scientist (Safe Control)
Builds
Core CBF algorithms for the Compass safety system
Domain
Robotics, Control Theory, Safety-Critical Systems
Deliverable
production ML models
Required skills
Control Barrier Functions, dynamical systems theory, nonlinear control, formal verification, C++, Python, real-time optimization, hybrid systems, model uncertainty handling
Preferred skills
Professional software development, hardware validation, functional safety standards (IEC 61508, ISO 13849, ISO 26262), real-time embedded systems, optimization-based controllers (QPs, SOCPs)
Technologies
C++, Python, QPs, SOCPs
Responsibilities
Develop and implement novel CBF algorithms; Compute and refine invariant sets for high-dimensional systems; Design formulations for hybrid dynamical systems; Address theory-to-practice gaps regarding uncertainty and noise; Create dynamics models; Implement real-time optimization solvers; Develop formal arguments for third-party certification; Validate algorithms via simulation and hardware experiments; Contribute to CBF theory through publications; Collaborate with perception, planning, and locomotion teams
Seniority
Senior, hands-on IC