Amazon
Applied Scientist, Safe Control, Amazon Robotics, Compass
$143K–$193K
PASADENA, CA +1 · Full-time · Posted Oct 12, 2026
- Location
- PASADENA, CA
Pasadena, CA - Experience
- PhD, or Master's degree and 4+ years of deep learning, computer vision, human robotic interaction, or algorithms implementation experience.
- Education
- PhD, or Master's degree
About the job
Develops Control Barrier Function algorithms and safety-critical control methods for reliable deployment across Amazon’s robot fleet.
What you'll do
- Develop and implement CBF algorithms, invariant sets, and hybrid-system formulations with formal safety guarantees.
- Build real-time control methods robust to uncertainty and hardware constraints, and validate them in simulation and on robots.
- Prepare safety arguments for third-party certification and contribute to CBF research publications.
What they ask for
- Deep expertise in Control Barrier Functions, including theory and practical implementation.
- Strong background in dynamical systems, nonlinear control, and formal verification or reachability analysis.
- Proficiency in C++ and Python, with experience implementing real-time control algorithms.
- Relevant publication record (e.g., CDC, ACC, ICRA, RSS, Automatica, TAC).
Nice to have
- Experience validating safety-critical algorithms on physical robots; professional software development experience.
- Experience with hybrid or robust control, functional safety standards, embedded systems, or optimization-based controllers.
Pay
142,800.00 - 193,200.00 USD annually (base salary)
Tools
Control Barrier Functions, C++, Python, IEC 61508, ISO 13849, ISO 26262, QPs, SOCPs
AI focus
Safety methods will integrate with motion planning, RL, and foundation models; backup-set approaches may leverage learned policies.
Model-written summary · the original posting is authoritative