h3Applied Scientist, Safe Control, Amazon Robotics, Compass /h3 pJob ID: | Amazon.com Services LLC /p pWe 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. A key challenge of this role is bridging the gap between the mathematics of set invariance and the realities of hardware, including sensor noise, model uncertainty, computational budgets, and discrete state transitions. /p pYou will ensure that these algorithms are not only provably correct but also implementable within a safety-critical architecture that must be certified by a third-party. You will contribute directly to the next generation of CBF theory and its practical deployment across Amazon's diverse robot fleet. /p pKey job responsibilities /p ul liDevelop and implement novel CBF algorithms that provide formal safety guarantees while minimizing conservatism to maximize the permissible operating envelope for each robot platform /li liCompute and refine invariant sets for complex, high-dimensional robotic systems, developing scalable methods that go beyond what existing analytical approaches can handle /li liDesign formulations for hybrid dynamical systems, handling discrete mode transitions (e.g., contact/no-contact, stance/flight phases) with provable safety across switching boundaries /li liAddress the theory-to-practice gap by developing methods that are robust to model uncertainty, sensor noise, actuation delays, and computational latency /li liCreate reduced-order and full-order dynamics models with both white-box and black-box approach /li liImplement real-time optimization solvers that execute within the tight timing budgets of safety-critical control loops /li liDevelop formal arguments and documentation sufficient to support third-party safety certification of algorithms /li liValidate algorithms through rigorous simulation and hardware experiments, characterizing failure modes and quantifying safety margins /li liContribute to the theoretical foundations of CBFs through publications at top-tier controls and robotics venues /li liCollaborate with perception, planning, locomotion, and manipulation teams to accommodate the needs of upstream and downstream systems /li /ul pA day in the life /p pAmazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: /p ul li1. Medical, Dental, and Vision Coverage /li li2. Maternity and Parental Leave Options /li li3. Paid Time Off (PTO) /li li4. 401(k) Plan /li /ul pIf you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, /p h3About the team /h3 pWork with the inventors of control barrier functions on a novel, universal approach to safe autonomy: one that scales across mobile robots, manipulators, mobile manipulators, and future robot platforms with dynamic stability. You'll push the boundary of safe performance by integrating safety with motion planning, RL, and foundation models, ensuring that safety is never a blocker to robot performance. Your work will underpin robots operating alongside people at Amazon's unprecendented scale. /p h3Basic Qualifications /h3 ul liPhD, or Master's degree and 4+ years of deep learning, computer vision, human robotic interaction, algorithms implementation experience /li liDeep expertise in Control Barrier Functions, including theoretical foundations and practical implementation /li liStrong mathematical background in dynamical systems theory, nonlinear control,



and formal verification or reachability analysis /li liProficiency in C++ and Python with experience implementing control algorithms for real-time systems /li liPublication record at relevant venues (e.g., CDC, ACC, ICRA, RSS, Automatica, TAC) /li /ul h3Preferred Qualifications /h3 ul liExperience in professional software development /li liExperience validating safety-critical algorithms on physical robotic hardware (not simulation-only) /li liExperience with hybrid systems theory and formulations that handle discrete transitions (e.g., contact events, mode switches) /li liExperience with robust or adaptive methods that account for parametric uncertainty or unmodeled dynamics /li liKnowledge of functional safety standards (IEC 61508, ISO 13849, ISO 26262) and experience preparing algorithms for third-party certification /li liFamiliarity with real-time embedded systems and the constraints of deploying optimization-based controllers on safety-rated hardware /li liExperience formulating and solving optimization-based controllers (QPs, SOCPs) for real-time safety filtering /li /ul pAmazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. /p pVeterans, military spouses, and people with disabilities are encouraged to apply. /p pThe base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life ADD insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at . /p pUSA, CA, PASADENA - 142,800.00 - 193,200.00 USD annually /p #J-18808-Ljbffr

📌 Applied Scientist, Safe Control, Amazon Robotics, Compass (Asti)
🏢 Amazon
📍 Asti